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Thoughts on the 2017 KDNuggets Poll on Data Science Tools

toast Thoughts on the 2017 KDNuggets Poll on Data Science Tools

Are you a data scientist and do not know KDNuggets.com?  How is this possible?  Ok, go there right now, add a bookmark, and make this part of your daily reading list.  But don’t forget to come back here afterwards to read the rest of this post.

KDNuggets is one of the most popular portals for data science, and is a great source for news and information.  It probably will not be winning a design award any time soon.  But the rich, deep content is why you will go back over and over, and that’s what really matters.

I spend more time on KDNuggets than usual in May, because that’s when the annual KDNuggets poll What data science solution did you use in the past 12 months? comes out. Gregory Piatetsky-Shapiro, the editor of KDNuggets and one of the best-known data scientists in the world, has been doing this poll for 18 years.

Gregory just published the results for 2017, and about 2,900 people have shared their software preferences for data science tools. And as always, there is a lot to learn from those results.

What’s new in data science in 2017?

First things first: RapidMiner was again voted as the most popular general data science platform and this is all thanks to our user community!  33% of all voters said that they are using RapidMiner, which is an amazing result. Many thanks to all of you!

But we know that data scientists are using up to 6 different tools in parallel so besides RapidMiner, what other tools are people using?

Let’s start with the programming languages. It should not come as a surprise that R and Python are the two leading languages for data science.  This year, Python got slightly more votes than R which might not be a significant difference really.  But in general Python has shown the bigger growth rates in the previous years, and I would not be surprised to see Python to take over the leading position over R in the future.  And then there is of course SQL, which made the third place among the programming languages.  SQL will of course never die, so no surprise here.

Connected to Python growth is Anaconda, a Python distribution with package management. Big shout out to our friends at Anaconda for growing that quickly!

On an infrastructure level, Apache Spark was used by 23% of all data scientists but Hadoop only by 7%.  And while we are talking about big data, the library MLLib only was used by 5% and hence much less than many other options.  To be honest, this was a bit of a surprise to me.

Deep Learning is all the rage

Yes, I am guilty for not playing along with the crazy deep learning hype of the past few years.  After all, the technology is much less innovative than most people believe. But I will admit that there is a strong growth trend around deep learning in our field.

This year, more than 32% of all data scientists said that they are using deep learning, up from 18% in 2016 and 9% in 2015.  Doubling every year is impressive growth indeed.

There are now a dozen or so deep learning libraries.  The most widely used one of course is Google’s Tensorflow, now used by 20% of all data scientists.

RapidMiner’s history with the KDNuggets poll

I view this poll a bit like a sporting event. It won’t make or break a vendor, but I at least take it serious. I think all vendors should take it seriously, and it looked like more vendors did this year.

The history of RapidMiner in the poll is interesting as well.  In 2006, our co-founder Ralf Klinkenberg was already why YALE was not an option in the poll (YALE was the former name of RapidMiner, and an acronym for “Yet Another Learning Environment”).  Who could know that only 11 years later machine learning would be all the hype?

RapidMiner was first included in the poll in 2007, and YALE was the most widely used open source platform from the start.  But some of our commercial competitors like SAS and SPSS were ahead of us back then.  But thanks to our loyal community and user base this changed quite quickly.  In 2008, we ended up just shy of SPSS Clementine (which later became SPSS Modeler).  We remained in the top 3 for a couple of years, and during that time other open source solutions like R started to gain more traction in the poll.

Starting In 2011, RapidMiner took over first place among all data science platform tools, and we have been able to keep this position since then.  One of the great things, however, is that data scientists now have many different approaches and often mix and match the different solutions.  There are clearly leading data science platforms like RapidMiner and in addition we have two great programming languages for data science as well, namely R and Python.

And then there are dozens of libraries like MLLib or Tensorflow, most of them accessible through RapidMiner as well.  So, you will be able to find the right tool for your problem and this is a wonderful situation to be in for data scientists.  Compare this to software offerings in the earlier years of this poll (check out the links above).

It’s a great time to be a data scientist indeed!

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Simultaneous Auto-growth in Multiple Files

SQL Server 2016 has a new configuration to control the auto-growth of multiple files in the same filegroup. When we create several files in the same filegroup SQL Server does a round robin across the files, writing a piece of data in each of them until all the data is finally on the files.

However, the amount of data written in each file may not be always the same. The algorithm SQL Server uses for the round robin takes into account the amount of free space in each file. Due to that, to ensure an even data distribution across the files, we need to keep the files with the same size.

If the auto-growth happens, one file will be bigger than the other, therefore the data distribution across the files will be unbalanced.

Starting in SQL Server 2016 we have a solution for this problem: The filegroups now have the “autogrow_all_files” attribute.  This attribute ensures that all files will grow together, keeping the same size.

Let’s execute a demo, step by step.

1) Create a new database. The statement below creates the database with two filegroups, the Primary and another one called FG1. You need to correct the path of the files before execute this statement.

CREATE DATABASE sales 

ON PRIMARY 

        (NAME = sales_dat, filename =
                ‘C:\MyFolder\Sales.mdf’, size = 8mb, maxsize = 500mb, filegrowth = 20% ),
filegroup fg1 — Default
        (NAME = sales_dat2, filename = ‘C:\MyFolder\Sales2.ndf’, size = 8mb, maxsize =
                 500mb, filegrowth = 20% ),

        (NAME = sales_dat3, filename =
                 ‘C:\MyFolder\Sales3.ndf’, size = 8mb, maxsize = 500mb, filegrowth = 20% )

log ON
        (NAME = sales_log, filename = ‘C:\MyFolder\Sales.ldf’, size = 20mb, maxsize =
                 unlimited, filegrowth = 10mb );
go 

2) Check the filegroups configuration. The result, in the image below, shows the default value of the attribute autogrow_all_files, disabled.

USE sales
go
SELECT NAME,is_autogrow_all_files
FROM   sys.filegroups 

AutogrowthAll05 Simultaneous Auto growth in Multiple Files

3) Let’s create a table in filegroup FG1, insert 2000 records and check the database files. The autogrowth didn’t happen yet.

CREATE TABLE test 
  (
     id    INT IDENTITY(1, 1) PRIMARY KEY,
     texto CHAR(8000)
  )
ON fg1
go
INSERT INTO test 
VALUES      (‘x’)
go 2000
EXEC Sp_helpfile
go 

AutogrowthAll02 Simultaneous Auto growth in Multiple Files

4) Using the DMV ‘sys.dm_db_database_page_allocations’ we can identify the data distribution across the files.

select extent_file_id,count(*)
 from
sys.dm_db_database_page_allocations
     (DB_ID(‘Sales’),OBJECT_ID(‘test’),1,1,‘DETAILED’)
group by extent_file_id

go

AutogrowthAll03 Simultaneous Auto growth in Multiple Files

5) Let’s insert more 20 records and check the files again. The auto-growth already happened in only one of the files.

insert into test values (‘x’)

go 20

exec sp_helpfile

AutogrowthAll04 Simultaneous Auto growth in Multiple Files

This result will unbalance the round-robin, reducing any advantage it’s creating for the environment. Let’s try the same demonstration again, this time changing the autogrow_all_files attribute of FG1 filegroup.

1) Drop and re-create the database, changing the autogrow_all_files and checking the change. Again, you need to correct the path of the files.

use master

go

drop databaseif exists Sales;

go

CREATE DATABASE Sales
 on Primary
  (NAME = Sales_dat, FILENAME = ‘C:\MyFolder\Sales.mdf’, SIZE = 8MB, MAXSIZE = 500MB, FILEGROWTH = 20% ),
 Filegroup FG1 — Default
  (NAME = Sales_dat2, FILENAME = ‘C:\MyFolder\Sales2.ndf’, SIZE = 8MB, MAXSIZE = 500MB, FILEGROWTH = 20% ),
  (NAME = Sales_dat3, FILENAME = ‘C:\MyFolder\Sales3.ndf’, SIZE = 8MB, MAXSIZE = 500MB, FILEGROWTH = 20% )
LOG ON
  (NAME = Sales_log, FILENAME = ‘C:\MyFolder\Sales.ldf’, SIZE = 20MB, MAXSIZE = UNLIMITED, FILEGROWTH = 10MB );

go

alter database Sales modify filegroup [FG1] AutoGrow_All_Files
      With Rollback Immediate

go

use sales

go

select name,is_autogrow_all_files
 from sys.filegroup

AutogrowthAll05 Simultaneous Auto growth in Multiple Files

2) Create the table, insert 2000 records and check the files.

create table test 
( id int identity(1,1) primary key,
  texto char(8000))
  on FG1

go

insert into test values (‘x’)

go 2000

exec sp_helpfile

go

AutogrowthAll06 Simultaneous Auto growth in Multiple Files

3) Insert 20 more records and check the files again. Now the auto-growth happened in both files, keeping the data distribution even across the files.

insert into test values (‘x’)

go 20 

exec sp_helpfile

AutogrowthAll07 Simultaneous Auto growth in Multiple Files

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SQL – Simple Talk

How To Use The Right Data At The Right Time For Better Customer Relationships

When it comes to buying things—even big-ticket items—the way we make decisions makes no sense. One person makes an impulsive offer on a house because of the way the light comes in through the kitchen windows. Another gleefully drives a high-end sports car off the lot even though it will probably never approach the limits it was designed to push.

We can (and usually do) rationalize these decisions after the fact by talking about needing more closet space or wanting to out-accelerate an 18-wheeler as we merge onto the highway, but years of study have arrived at a clear conclusion:

When it comes to the customer experience, human beings are fundamentally irrational.

In the brick-and-mortar past, companies could leverage that irrationality in time-tested ways. They relied heavily on physical context, such as an inviting retail space, to make products and services as psychologically appealing as possible. They used well-trained salespeople and employees to maximize positive interactions and rescue negative ones. They carefully sequenced customer experiences, such as having a captain’s dinner on the final night of a cruise, to play on our hard-wired craving to end experiences on a high note.

sap Q217 digital double feature1 images1 How To Use The Right Data At The Right Time For Better Customer Relationships

Today, though, customer interactions are increasingly moving online. Fortune reports that on 2016’s Black Friday, the day after Thanksgiving that is so crucial to holiday retail results, 108.5 million Americans shopped online, while only 99.1 million visited brick-and-mortar stores. The 9.4% gap between the two was a dramatic change from just one year prior, when on- and offline Black Friday shopping were more or less equal.

When people browse in a store for a few minutes, an astute salesperson can read the telltale signs that they’re losing interest and heading for the exit. The salesperson can then intervene, answering questions and closing the sale.

Replicating that in a digital environment isn’t as easy, however. Despite all the investments companies have made to counteract e-shopping cart abandonment, they lack the data that would let them anticipate when a shopper is on the verge of opting out of a transaction, and the actions they take to lure someone back afterwards can easily come across as less helpful than intrusive.

In a digital environment, companies need to figure out how to use Big Data analysis and digital design to compensate for the absence of persuasive human communication and physical sights, sounds, and sensations. What’s more, a 2014 Gartner survey found that 89% of marketers expected customer experience to be their primary differentiator by 2016, and we’re already well into 2017.

As transactions continue to shift toward the digital and omnichannel, companies need to figure out new ways to gently push customers along the customer journey—and to do so without frustrating, offending, or otherwise alienating them.

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The quest to understand online customers better in order to influence them more effectively is built on a decades-old foundation: behavioral psychology, the study of the connections between what people believe and what they actually do. All of marketing and advertising is based on changing people’s thoughts in order to influence their actions. However, it wasn’t until 2001 that a now-famous article in the Harvard Business Review formally introduced the idea of applying behavioral psychology to customer service in particular.

The article’s authors, Richard B. Chase and Sriram Dasu, respectively a professor and assistant professor at the University of Southern California’s Marshall School of Business, describe how companies could apply fundamental tenets of behavioral psychology research to “optimize those extraordinarily important moments when the company touches its customers—for better and for worse.” Their five main points were simple but have proven effective across multiple industries:

  1. Finish strong. People evaluate experiences after the fact based on their high points and their endings, so the way a transaction ends is more important than how it begins.
  2. Front-load the negatives. To ensure a strong positive finish, get bad experiences out of the way early.
  3. Spread out the positives. Break up the pleasurable experiences into segments so they seem to last longer.
  4. Provide choices. People don’t like to be shoved toward an outcome; they prefer to feel in control. Giving them options within the boundaries of your ability to deliver builds their commitment.
  5. Be consistent. People like routine and predictability.

For example, McKinsey cites a major health insurance company that experimented with this framework in 2009 as part of its health management program. A test group of patients received regular coaching phone calls from nurses to help them meet health goals.

The front-loaded negative was inherent: the patients knew they had health problems that needed ongoing intervention, such as weight control or consistent use of medication. Nurses called each patient on a frequent, regular schedule to check their progress (consistency and spread-out positives), suggested next steps to keep them on track (choices), and cheered on their improvements (a strong finish).

McKinsey reports the patients in the test group were more satisfied with the health management program by seven percentage points, more satisfied with the insurance company by eight percentage points, and more likely to say the program motivated them to change their behavior by five percentage points.

sap Q217 digital double feature1 images2 How To Use The Right Data At The Right Time For Better Customer Relationships

The nurses who worked with the test group also reported increased job satisfaction. And these improvements all appeared in the first two weeks of the pilot program, without significantly affecting the company’s costs or tweaking key metrics, like the number and length of the calls.

Indeed, an ongoing body of research shows that positive reinforcements and indirect suggestions influence our decisions better and more subtly than blatant demands. This concept hit popular culture in 2008 with the bestselling book Nudge.

Written by University of Chicago economics professor Richard H. Thaler and Harvard Law School professor Cass R. Sunstein, Nudge first explains this principle, then explores it as a way to help people make decisions in their best interests, such as encouraging people to eat healthier by displaying fruits and vegetables at eye level or combatting credit card debt by placing a prominent notice on every credit card statement informing cardholders how much more they’ll spend over a year if they make only the minimum payment.

Whether they’re altruistic or commercial, nudges work because our decision-making is irrational in a predictable way. The question is how to apply that awareness to the digital economy.

sap Q217 digital double feature1 images7 1024x572 How To Use The Right Data At The Right Time For Better Customer Relationships

In its early days, digital marketing assumed that online shopping would be purely rational, a tool that customers would use to help them zero in on the best product at the best price. The assumption was logical, but customer behavior remained irrational.

Our society is overloaded with information and short on time, says Brad Berens, Senior Fellow at the Center for the Digital Future at the University of Southern California, Annenberg, so it’s no surprise that the speed of the digital economy exacerbates our desire to make a fast decision rather than a perfect one, as well as increasing our tendency to make choices based on impulse rather than logic.

sap Q217 digital double feature1 images3 How To Use The Right Data At The Right Time For Better Customer Relationships

Buyers want what they want, but they don’t necessarily understand or care why they want it. They just want to get it and move on, with minimal friction, to the next thing. “Most of our decisions aren’t very important, and we only have so much time to interrogate and analyze them,” Berens points out.

But limited time and mental capacity for decision-making is only half the issue. The other half is that while our brains are both logical and emotional, the emotional side—also known as the limbic system or, more casually, the primitive lizard brain—is far older and more developed. It’s strong enough to override logic and drive our decisions, leaving rational thought to, well, rationalize our choices after the fact.

This is as true in the B2B realm as it is for consumers. The business purchasing process, governed as it is by requests for proposals, structured procurement processes, and permission gating, is designed to ensure that the people with spending authority make the most sensible deals possible. However, research shows that even in this supposedly rational process, the relationship with the seller is still more influential than product quality in driving customer commitment and loyalty.

sap Q217 digital double feature1 images8 1024x572 How To Use The Right Data At The Right Time For Better Customer Relationships

Baba Shiv, a professor of marketing at Stanford University’s Graduate School of Business, studies how the emotional brain shapes decisions and experiences. In a popular TED Talk, he says that people in the process of making decisions fall into one of two mindsets: Type 1, which is stressed and wants to feel comforted and safe, and Type 2, which is bored or eager and wants to explore and take action.

People can move between these two mindsets, he says, but in both cases, the emotional brain is in control. Influencing it means first delivering a message that soothes or motivates, depending on the mindset the person happens to be in at the moment and only then presenting the logical argument to help rationalize the action.

In the digital economy, working with those tendencies means designing digital experiences with the full awareness that people will not evaluate them objectively, says Ravi Dhar, director of the Center for Customer Insights at the Yale School of Management. Since any experience’s greatest subjective impact in retrospect depends on what happens at the beginning, the end, and the peaks in between, companies need to design digital experiences to optimize those moments—to rationally design experiences for limited rationality.

This often involves making multiple small changes in the way options are presented well before the final nudge into making a purchase. A paper that Dhar co-authored for McKinsey offers the example of a media company that puts most of its content behind a paywall but offers free access to a limited number of articles a month as an incentive to drive subscriptions.

Many nonsubscribers reached their limit of free articles in the morning, but they were least likely to respond to a subscription offer generated by the paywall at that hour, because they were reading just before rushing out the door for the day. When the company delayed offers until later in the day, when readers were less distracted, successful subscription conversions increased.

Pre-selecting default options for necessary choices is another way companies can design digital experiences to follow customers’ preference for the path of least resistance. “We know from a decade of research that…defaults are a de facto nudge,” Dhar says.

For example, many online retailers set a default shipping option because customers have to choose a way to receive their packages and are more likely to passively allow the default option than actively choose another one. Similarly, he says, customers are more likely to enroll in a program when the default choice is set to accept it rather than to opt out.

Another intriguing possibility lies in the way customers react differently to on-screen information based on how that information is presented. Even minor tweaks can have a disproportionate impact on the choices people make, as explained in depth by University of California, Los Angeles, behavioral economist Shlomo Benartzi in his 2015 book, The Smarter Screen.

A few of the conclusions Benartzi reached: items at the center of a laptop screen draw more attention than those at the edges. Those on the upper left of a screen split into quadrants attract more attention than those on the lower left. And intriguingly, demographics are important variables.

Benartzi cites research showing that people over 40 prefer more visually complicated, text-heavy screens than younger people, who are drawn to saturated colors and large images. Women like screens that use a lot of different colors, including pastels, while men prefer primary colors on a grey or white background. People in Malaysia like lots of color; people in Germany don’t.

This suggests companies need to design their online experiences very differently for middle-aged women than they do for teenage boys. And, as Benartzi writes, “it’s easy to imagine a future in which each Internet user has his or her own ‘aesthetic algorithm,’ customizing the appearance of every site they see.”

Applying behavioral psychology to the digital experience in more sophisticated ways will require additional formal research into recommendation algorithms, predictions, and other applications of customer data science, says Jim Guszcza, PhD, chief U.S. data scientist for Deloitte Consulting.

In fact, given customers’ tendency to make the fastest decisions, Guszcza believes that in some cases, companies may want to consider making choice environments more difficult to navigate— a process he calls “disfluencing”—in high-stakes situations, like making an important medical decision or an irreversible big-ticket purchase. Choosing a harder-to-read font and a layout that requires more time to navigate forces customers to work harder to process the information, sending a subtle signal that it deserves their close attention.

That said, a company can’t apply behavioral psychology to deliver a digital experience if customers don’t engage with its site or mobile app in the first place. Addressing this often means making the process as convenient as possible, itself a behavioral nudge.

A digital solution that’s easy to use and search, offers a variety of choices pre-screened for relevance, and provides a friction-free transaction process is the equivalent of putting a product at eye level—and that applies far beyond retail. Consider the Global Entry program, which streamlines border crossings into the U.S. for pre-approved international travelers. Members can skip long passport control lines in favor of scanning their passports and answering a few questions at a touchscreen kiosk. To date, 1.8 million people have decided this convenience far outweighs the slow pace of approvals.

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The basics of influencing irrational customers are essentially the same whether they’re taking place in a store or on a screen. A business still needs to know who its customers are, understand their needs and motivations, and give them a reason to buy.

And despite the accelerating shift to digital commerce, we still live in a physical world. “There’s no divide between old-style analog retail and new-style digital retail,” Berens says. “Increasingly, the two are overlapping. One of the things we’ve seen for years is that people go into a store with their phones, shop for a better price, and buy online. Or vice versa: they shop online and then go to a store to negotiate for a better deal.”

Still, digital increases the number of touchpoints from which the business can gather, cluster, and filter more types of data to make great suggestions that delight and surprise customers. That’s why the hottest word in marketing today is omnichannel. Bringing behavioral psychology to bear on the right person in the right place in the right way at the right time requires companies to design customer experiences that bridge multiple channels, on- and offline.

Amazon, for example, is known for its friction-free online purchasing. The company’s pilot store in Seattle has no lines or checkout counters, extending the brand experience into the physical world in a way that aligns with what customers already expect of it, Dhar says.

Omnichannel helps counter some people’s tendency to believe their purchasing decision isn’t truly well informed unless they can see, touch, hear, and in some cases taste and smell a product. Until we have ubiquitous access to virtual reality systems with full haptic feedback, the best way to address these concerns is by providing personalized, timely, relevant information and feedback in the moment through whatever channel is appropriate. That could be an automated call center that answers frequently asked questions, a video that shows a product from every angle, or a demonstration wizard built into the product. Any of these channels could also suggest the customer visit the nearest store to receive help from a human.

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The omnichannel approach gives businesses plenty of opportunities to apply subtle nudges across physical and digital channels. For example, a supermarket chain could use store-club card data to push personalized offers to customers’ smartphones while they shop. “If the data tells them that your goal is to feed a family while balancing nutrition and cost, they could send you an e-coupon offering a discount on a brand of breakfast cereal that tastes like what you usually buy but contains half the sugar,” Guszcza says.

Similarly, a car insurance company could provide periodic feedback to policyholders through an app or even the digital screens in their cars, he suggests. “Getting a warning that you’re more aggressive than 90% of comparable drivers and three tips to avoid risk and lower your rates would not only incentivize the driver to be more careful for financial reasons but reduce claims and make the road safer for everyone.”

Digital channels can also show shoppers what similar people or organizations are buying, let them solicit feedback from colleagues or friends, and read reviews from other people who have made the same purchases. This leverages one of the most familiar forms of behavioral psychology—reinforcement from peers—and reassures buyers with Shiv’s Type 1 mindset that they’re making a choice that meets their needs or encourages those with the Type 2 mindset to move forward with the purchase. The rational mind only has to ask at the end of the process “Am I getting the best deal?” And as Guszcza points out, “If you can create solutions that use behavioral design and digital technology to turn my personal data into insight to reach my goals, you’ve increased the value of your engagement with me so much that I might even be willing to pay you more.”

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Many transactions take place through corporate procurement systems that allow a company to leverage not just its own purchasing patterns but all the data in a marketplace specifically designed to facilitate enterprise purchasing. Machine learning can leverage this vast database of information to provide the necessary nudge to optimize purchasing patterns, when to buy, how best to negotiate, and more. To some extent, this is an attempt to eliminate psychology and make choices more rational.

B2B spending is tied into financial systems and processes, logistics systems, transportation systems, and other operational requirements in a way no consumer spending can be. A B2B decision is less about making a purchase that satisfies a desire than it is about making a purchase that keeps the company functioning.

That said, the decision still isn’t entirely rational, Berens says. When organizations have to choose among vendors offering relatively similar products and services, they generally opt for the vendor whose salespeople they like the best.

This means B2B companies have to make sure they meet or exceed parity with competitors on product quality, pricing, and time to delivery to satisfy all the rational requirements of the decision process. Only then can they bring behavioral psychology to bear by delivering consistently superior customer service, starting as soon as the customer hits their app or website and spreading out positive interactions all the way through post-purchase support. Finishing strong with a satisfied customer reinforces the relationship with a business customer just as much as it does with a consumer.

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The best nudges make the customer relationship easy and enjoyable by providing experiences that are effortless and fun to choose, on- or offline, Dhar says. What sets the digital nudge apart in accommodating irrational customers is its ability to turn data about them and their journey into more effective, personalized persuasion even in the absence of the human touch.

Yet the subtle art of influencing customers isn’t just about making a sale, and it certainly shouldn’t be about persuading people to act against their own best interests, as Nudge co-author Thaler reminds audiences by exhorting them to “nudge for good.”

Guszcza, who talks about influencing people to make the choices they would make if only they had unlimited rationality, says companies that leverage behavioral psychology in their digital experiences should do so with an eye to creating positive impact for the customer, the company, and, where appropriate, the society.

In keeping with that ethos, any customer experience designed along behavioral lines has to include the option of letting the customer make a different choice, such as presenting a confirmation screen at the end of the purchase process with the cold, hard numbers and letting them opt out of the transaction altogether.

“A nudge is directing people in a certain direction,” Dhar says. “But for an ethical vendor, the only right direction to nudge is the right direction as judged by the customers themselves.” D!

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.


About the Authors:

Volker Hildebrand is Global Vice President for SAP Hybris solutions.

Sam Yen is Chief Design Officer and Managing Director at SAP.

Fawn Fitter is a freelance writer specializing in business and technology.

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Memory optimized table variable and cardinality estimate

In a previous blog, I talked about memory optimized table consumes memory until end of the batch.   In this blog, I want to make you aware of cardinality estimate of memory optimized table as we have had customers who called in for clarifications.  By default memory optimized table variable behaves the same way as disk based table variable. It will have 1 row as an estimate.   In disk based table variable, you can control estimate by using option (recompile) at statement level (see this blog) or use trace flag 2453

You can control the same behavior using the two approaches on memory optimized table variable if you use it in an ad hoc query or inside a regular TSQL stored procedure.  The behavior will be the same. This little repro will show the estimate is correct with option (recompile).

create database IMOLTP
go
ALTER DATABASE imoltp ADD FILEGROUP imoltp_mod CONTAINS MEMORY_OPTIMIZED_DATA 
go
ALTER DATABASE imoltp ADD FILE (name=’imoltp_mod1′, filename=’c:\sqldata\imoltp_mod2′) TO FILEGROUP imoltp_mod 
go

use IMOLTP
go

CREATE TYPE dbo.test_memory AS TABLE
(c1 INT NOT NULL INDEX ix_c1,
c2 CHAR(10))
WITH (MEMORY_OPTIMIZED=ON);


go

DECLARE @tv dbo.test_memory
set nocount on

declare @i int
set @i = 1
while @i < 10000
begin
    insert into @tv values (@i, ‘n’)
    set @i = @i + 1
end
set statistics xml on
–this will work and the etimate will be correct
select * from @tv t1 join @tv t2 on t1.c1=t2.c1 option (recompile, querytraceon 2453)
set statistics xml off
go

image thumb152 Memory optimized table variable and cardinality estimate

But the problem occurs when you use it inside a natively compiled stored procedure.  In this case, it will always estimate 1 row.  You can’t change it because natively compiled procedure doesn’t allow statement level recompile.  If you try to create a natively compiled procedure, you will get errors that disallow you to create the procedure.


create procedure test
with native_compilation, schemabinding 
as  
begin atomic with 
(transaction isolation level = snapshot, 
language = N’English’) 

DECLARE @tv dbo.test_memory
declare @i int
set @i = 1
while @i < 10000
begin
    insert into @tv values (@i, ‘n’)
    set @i = @i + 1
end
–you can’t add TF 3453 or recompile
select t1.c1, t2.c1 from @tv t1 join @tv t2 on t1.c1=t2.c1 option (recompile, querytraceon 2453)
end 
go


Msg 10794, Level 16, State 45, Procedure test, Line 17 [Batch Start Line 39]
The query hint ‘RECOMPILE’ is not supported with natively compiled modules.
Msg 10794, Level 16, State 45, Procedure test, Line 17 [Batch Start Line 39]
The query hint ‘QUERYTRACEON’ is not supported with natively compiled modules.

So that is the solution?   For natively compiled procedure, here are some advices

1. limit number of rows inserted into the memory optimized table variable.

2. if you are joining with memory optimized table variable that has lots of rows, consider use a schema_only memory optimized table

3. if  you know your data, you can potentially re-arrange the join and use option (force order) to get around it.

Jack Li |Senior Escalation Engineer | Microsoft SQL Server

twitter| pssdiag |Sql Nexus

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CSS SQL Server Engineers

Combining Midi Files

 Combining Midi Files

I have a list of imported midi files, as Sound objects. I simply want to string them together, with a pause of 0.5 seconds between each one. I’ve tried a lot of things and nothing has worked, apart from a hack-y version of manipulating the midi’s as strings, which is needlessly over complicated.

Is there an easy way to combine sound objects like this?

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Connecting Apache Zeppelin to your Oracle Data Warehouse

 Connecting Apache Zeppelin to your Oracle Data Warehouse

In my last posts I provided an overview of the Apache Zeppelin open source project which is a new style of application called a “notebook”. These notebook applications typically runs within your browser so as an end user there is no desktop software to download and install.

Interestingly, I had a very quick response to this article asking about how to setup a connection within Zeppelin to an Oracle Database. Therefore, in this post I am going to look at how you can install the Zeppelin server and create a connection to your Oracle data warehouse.

This aim of this post is to walk you through the following topics:

  • Installing Zeppelin
  • Configuring Zeppelin
  • What is an interpreter
  • Finding and installing the Oracle JDBC drivers
  • Setting up a connection to an Oracle PDB

Firstly a quick warning! There are a couple of different versions of Zeppelin available for download. At the moment I am primarily using version 0.6.2 which works really well. Currently, for some reason I am seeing performance problems with the latest iterations around version 0.7.x and this issue. I have discussed this a few people here at Oracle and we are all seeing the same behaviour – queries will run, they just take 2-3 minutes longer for some unknown reason compared with earlier versions, pre-0.7.x, of Zeppelin.

In the interests of completeness in this post I will cover setting up a 0.6.2 instance of Zeppelin as well as a 0.7.1 instance.

Installing Zeppelin

The first thing you need to decide is where to install the Zeppelin software. You can run on your own PC or on a separate server or on the same server that is running your Oracle Database. I run all my linux based database environments within Virtualbox images so I always install onto the same virtual machine as my Oracle database – makes life easier for moving demos around when I am heading off to user conference.

Step two is to download the software. The download page is here: https://zeppelin.apache.org/download.html.

Simply pick the version you want to run and download the corresponding compressed file – my recommendation, based on my experience, is to stick with version 0.6.2 which was released on Oct 15, 2016. I always select to download the full application – “Binary package with all interpreters” just to make life easy and it also gives me access the full range of connection options which, as you will discover in my next post, is extremely useful.

Installing Zeppelin – Version 0.6.2

After downloading the zeppelin-0.6.2-bin-all.tgz file onto my Linux Virtualbox machine I simply expand the file to create a “zeppelin-0.6.2-bin-all” directory. The resulting directory structure looks like this:

 Connecting Apache Zeppelin to your Oracle Data Warehouse

Of course you can rename the folder name to something more meaningful, such as “my-zeppelin” if you wish….obviously, the underlying folder structure remains the same!

 Connecting Apache Zeppelin to your Oracle Data Warehouse

Installing Zeppelin – Version 0.7.x

The good news is that if you want to install one of the later versions of Zeppelin then the download and unzip process is exactly the same. At this point in time there are two versions of 0.7, however, both 0.7.0 and 0.7.1 seem to suffer from poor query performance when using the JDBC driver (I have only tested the JDBC driver against Oracle Database but I presume the same performance issues are affecting other types of JDBC-related connections). As with the previous version of Zeppelin you can, if required, change the default directory name to something more suitable.
Now we have our notebook software unpacked and ready to go!

Configuring Zeppelin (0.6.2 and 0.7.x)

This next step is optional. If you have installed the Zeppelin software on the same server or virtual environment that runs your Oracle Database then you will need to tweak the default configuration settings to ensure there are no clashes with the various Oracle Database services. By default, you access the Zeppelin Notebook home page via the port 8080. Depending on your database environment this may or may not cause problems. In my case, this port was already being used by APEX, therefore, it was necessary to change the default port…

Configuring the Zeppelin http port

If you look inside the “conf” directory there will be a file named “zeppelin-site.xml.template”, rename this to “zeppelin-site.xml”. Find the following block of tags:

zeppelin.server.port8080Server port.

the default port settings in the conf file will probably clash with the APEX environment in your Oracle Database. Therefore, you will need to change the port setting to another value, such as:

zeppelin.server.port7081Server port.


Save the file and we are ready to go! It is worth spending some time reviewing the other settings within the conf file that let you use cloud storage services, such as the Oracle Bare Metal Cloud Object Storage service. For my purposes I was happy to accept the default storage locations for managing my notebooks and I have not tried to configure the use of an SSL service to manage client authentication. Obviously, there is a lot more work that I need to do around the basic setup and configuration procedures which hopefully I will be able to explore at some point in time – watch this space!

OK, now we have everything in place: software, check…. port configuration, check. It’s time to start your engine!

Starting Zeppelin

This is the easy part. Within the bin directory there is a shell script to run the Zeppelin daemon:

. ../my-zeppelin/bin/zeppelin-daemon.sh start


There is a long list of command line environment settings that you can use, see here: https://zeppelin.apache.org/docs/0.6.2/install/install.html. In my Virtualbox environment I found it useful to configure the following settings:

  • ZEPPELIN_MEM: amount of memory available to Zeppelin. The default setting is – -Xmx1024m -XX:MaxPermSize=512m
  • ZEPPELIN_INTP_MEM: amount of memory available to the Zeppelin Interpreter (connection) engine and the default setting is derived from the setting of ZEPPELIN_MEM
  • ZEPPELIN_JAVA_OPTS: simply lists any additional JVM options

 therefore, my startup script looks like this:

set ZEPPELIN_MEM=-Xms1024m -Xmx4096m -XX:MaxPermSize=2048m
set ZEPPELIN_INTP_MEM=-Xms1024m -Xmx4096m -XX:MaxPermSize=2048m
set ZEPPELIN_JAVA_OPTS="-Dspark.executor.memory=8g -Dspark.cores.max=16"
. ../my-zeppelin/bin/zeppelin-daemon.sh start
 

 Fingers crossed, once Zeppelin has started the following message should appear on your command line:

 Zeppelin start                                             [  OK  ]

Connecting to Zeppelin

Everything should now be in place to test whether your Zeppelin environment is up and running. Open a browser and type the ip address/host name and port reference which in my case is: http://localhost:7081/#/ then the home page should appear:

 Connecting Apache Zeppelin to your Oracle Data Warehouse

The landing pad interface is nice and simple.

In the top right-hand corner you will see a green light which tells me that the Zeppelin service is up and running. “anonymous” is my user id because I have not enabled client side authentication. In the main section of the welcome screen you will see links to the help system and the community pages, which is where you can log any issues that you find.

The Notebook section is where all the work is done and this is where I am going to spend the next post exploring in some detail. If you are used using a normal BI tool then Zeppelin (along with most other notebook applications) will take some getting used to because it creating reports follows is more of scripting-style process rather than a wizard-driven click-click process you get with products like Oracle Business Intelligence. Anyway, more on this later,

What is an Interpreter?

To build notebooks in Zeppelin you need to make connections to your data sources. This is done using something called an “Interpreter”. This is a plug-in which enables Zeppelin to use not only a specific query language but also provides access to backend data-processing capabilities. For example, it is possible to include shell scripting code within a Zeppelin notebook by using the %sh interpreter. To access an Oracle Database we use the JDBC interpreter. Obviously, you might want to have lots of different JDBC-based connections – maybe you have an Oracle 11g instance, a 12cR1 instance and a 12c R2 instance. Zeppelin allows you to create new interpreters and define their connection characteristics.

It’s at this point that version 0.6.2 and versions 0.7.x diverge. Each has its own setup and configuration process for interpreters so I will explain the process for each version separately. Firstly, we need to track down some JDBC files…

Configuring your JDBC files

Finally, we have reached the point of this post – connecting Zeppelin to your Oracle data warehouse. But before we dive into setting up connections we need to track down some Oracle specific jdbc files. You will need to locate one of the following files to use with Zeppelin: ojdbc7.jar  (Database 12c Release 1) or ojdbc8.jar (Database 12c Release 2).

You can either copy the relevant file to your Zeppelin server or simply point the Zeppelin interpreter to the relevant directory. My preference is to keep everything contained within the Zeppelin folder structure so I have taken my Oracle JDBC files and moved them to my Zeppelin server. If you want to find the JDBC files that come with your database version then you need to find the jdbc folder within your version-specific folder. In my 12c Release 2 environment this was located in the folder shown below:

 Connecting Apache Zeppelin to your Oracle Data Warehouse

alternatively, I could have copied the files from my local SQL Developer installation:

 Connecting Apache Zeppelin to your Oracle Data Warehouse

take the jdbc file(s) and copy them to the /interpreter/jdbc directory within your Zeppelin installation directory, as shown below:

 Connecting Apache Zeppelin to your Oracle Data Warehouse

Creating an Interpreter for Oracle Database

At last we are finally ready to create a connection to our Oracle Database! Make a note of the directory containing the Oracle JDBC file because you will need that information during the configuration process. There is a difference between the different versions of Zeppelin in terms of creating a connection to an Oracle database/PDB.

Personally, I think the process in version 0.7.x makes more sense but the performance of jdbc is truly dreadful for some reason. There is obviously been a major change of approach in terms of how connections are managed within Zeppelin and this seems to causing a few issues. Digging around in the documentation it would appear that 0.8.x version will be available shortly so I am hoping the version 0.7x connection issues will be resolved!

Process for creating a connection using version 0.6.2

Starting from the home page (just click on the word “Zeppelin” in the top left corner of your browser or open a new window and connect to http://localhost:7081/#/), then click on the username “anonymous” which will reveal a pulldown menu. Select “Interpreter” as shown below:

 Connecting Apache Zeppelin to your Oracle Data Warehouse

this will take you to the home page for managing your connections, or interpreters. Each query language and data processing language has its own interpreter and these are all listed in alphabetical order.

 Connecting Apache Zeppelin to your Oracle Data Warehouse

scroll down until you find the entry for jdbc:

 Connecting Apache Zeppelin to your Oracle Data Warehouse

here you will see that the jdbc interpreter is already configured for two separate connections: postgres and hive. By clicking on the “edit” button on the right-hand side we can add new connection attributes and in this case I have removed the hive and postgres attributes and added new attributes

  • osql.driver
  • osql.password
  • osql.url
  • osql.user

the significance of the “osql.” prefix will become obvious when we start to build our notebooks – essentially this will be our reference to these specific connection details. I have added a dependency by including an artefact that points to the location of my jdbc file. In the screenshot below you will see that I am connecting to the example sales history schema owned by user sh, password sh, which I have installed in my pluggable database dw2pdb2. The listener port for my jdbc connection is 1521.

If you have access to SQL Developer then an easy solution for testing your connection details is to setup a new connection and run the test connection routine. If SQL Developer connects to your database/pdb using your jdbc connection string then Zeppelin should also be able to connect successfully. FYI…error messages in Zeppelin are usually messy and long listings of a Java program stack. Not easy to workout where the problem actually originates. Therefore, the more you can test outside of Zeppelin the easier life will be – at least that is what I have found!

Below is my enhanced configuration for the jdbc interpreter:

 Connecting Apache Zeppelin to your Oracle Data Warehouse

The default.driver is simply the entry point into the Oracle jdbc driver which is oracle.jdbc.driver.OracleDriver. The last task is to add an artifact [sic] that points to the location of the Oracle JDBC file. In this case I have pointed to the 12c Release 1 driver stored in the ../zeppelin/intepreter/jdbc folder.

Process for creating a connection using version 0.7.x

As before, starting from the home page (just click on the word “Zeppelin” in the top left corner of your browser or open a new window and connect to http://localhost:7081/#/), then click on the username “anonymous” which will reveal a pulldown menu shown below:
 Connecting Apache Zeppelin to your Oracle Data Warehouse

now with version 0.7.0 and 0.7.1 we need to actually create a new interpreter, therefore, just click on the “+Create” button:

 Connecting Apache Zeppelin to your Oracle Data Warehouse

this will bring up the “Create new interpreter” form that will allow you to define the attributes for the new interpreter:

 Connecting Apache Zeppelin to your Oracle Data Warehouse

I will name my new interpreter “osql” and assign it to the JDBC group:

 Connecting Apache Zeppelin to your Oracle Data Warehouse

this will pre-populate the form with the default attributes needed to define a JDBC-type connection such as:

  • default.driver: driver entry point into the Oracle JDBC driver
  • default.password: Oracle user password
  • default.url: JDBC connection string to access the Oracle database/pDB 
  • default.user: Oracle username

the initial form will look like this:

 Connecting Apache Zeppelin to your Oracle Data Warehouse

and in my case I need to connect to a PDB called dw2pdb2 on the same server accessed via the listener port 1521, the username is sh and the password is sh. The only non-obvious entry is the default.driver which is oracle.jdbc.driver.OracleDriver. As before, the last task is to add an artifact [sic] that points to the location of the Oracle JDBC file. In this case I have pointed to the 12c Release 2 driver stored in the ../zeppelin/intepreter/jdbc folder.

Once you have entered the configuration settings, hit Save and your form should look like this:

 Connecting Apache Zeppelin to your Oracle Data Warehouse
 

Testing your new interpreter

To test the your interpreter will successfully connect to your database/pdb and run a SQL statement we need to create a new notebook. Go back to the home page and click on the “Create new note” link in the list on the left side of the screen.

 Connecting Apache Zeppelin to your Oracle Data Warehouse

Enter a name for your new note:

 Connecting Apache Zeppelin to your Oracle Data Warehouse

which will bring you to the notebook screen which is where you write your scripts – in this case SQL statements. This is similar in layout and approach as many worksheet-based tools (SQL Developer, APEX SQL Worksheet etc etc). If you are using version 0.6.x of Zeppelin then you can bypass the following…

If you are using version 0.7.x then we have to bind our SQL interpreter (osql) to this new note which will allow us to run SQL commands against the sh schema. To add the osql interpreter simply click on the gear icon in the top right-hand side of the screen:

 Connecting Apache Zeppelin to your Oracle Data Warehouse

this will then show you the list of interpreters which are available to this new note. You can switch interpreters on and off by clicking on them and for this example I have reduced the number of interpreters to just the following: markup (md), shell scripting (sh), file management (file), our Oracle SH pdb connection (osq) and jdbc connections (jdbc). Once you are done, click on the “Save” button to return to the note.

I will explain the layout the of the note interface in my next post. For the purposes of testing the connection to my pdb I need to use the “osql” interpreter and give it a SQL statement to run. This is two-lines of code as shown here

 Connecting Apache Zeppelin to your Oracle Data Warehouse

On the right side of the screen there is a triangle icon which is will execute or “Run” my SQL statement:

SELECT sysdate FROM dual


 Connecting Apache Zeppelin to your Oracle Data Warehouse

note that I have not included a semi-colon (;) at the end of the SQL statement! In version 0.6.2 if you include the semi-colon (;) you will get a java error. Version 0.7x is a little more tolerant and does not object to having or not having a semi-colon (;).

Using my Virtualbox environment the first time I make a connection to execute a SQL statement the query takes 2-3 minutes to establish the connection to my PDB and then run the query. This is true even for simple queries such as SELECT * FROM dual. Once the first query has completed then all subsequent queries run in the normal expected timeframe (i.e. around the same time as executing the query from within SQL Developer).

Eventually, the result will be displayed. By default, output is shown in tabular layout (as you can see from the list of available icons, “graph-based layouts are also available

 Connecting Apache Zeppelin to your Oracle Data Warehouse

…and we have now established that the connection to our SH schema is working.

Summary

In this post we have covered the following topics:

  • How to install Zeppelin
  • How configure and start Zeppelin
  • Finding and installing the correct Oracle JDBC drivers
  • Set up a connection to an Oracle PDB and tested the connection

As we have seen during this post, there are some key differences between the 0.6.x and 0.7.x versions of Zeppelin in terms of the way interpreters (connections) are defined. Now we have a fully working environment (Zeppelin connected to my Oracle 12c Release 2 PDB which includes sales history sample schema).

Therefore, in my next post I am going to look at how you can use the powerful notebook interface to access remote data files, load data into a schema, create both tabular and graph-based reports, briefing books and even design simple dashboards. Stay tuned for more information about how to use Zeppelin with Oracle Database.

If you are already using Zeppelin against your Oracle Database and would like to share your experiences that would be great – please use the comments feature below or feel free to send me an email: keith.laker@oracle.com.

(image at top of post is courtesy of wikipedia)
 

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Oracle Blogs | Oracle The Data Warehouse Insider Blog

Top Ten Digitalist Magazine Posts Of The Week [May 22, 2017]

When it comes to buying things—even big-ticket items—the way we make decisions makes no sense. One person makes an impulsive offer on a house because of the way the light comes in through the kitchen windows. Another gleefully drives a high-end sports car off the lot even though it will probably never approach the limits it was designed to push.

We can (and usually do) rationalize these decisions after the fact by talking about needing more closet space or wanting to out-accelerate an 18-wheeler as we merge onto the highway, but years of study have arrived at a clear conclusion:

When it comes to the customer experience, human beings are fundamentally irrational.

In the brick-and-mortar past, companies could leverage that irrationality in time-tested ways. They relied heavily on physical context, such as an inviting retail space, to make products and services as psychologically appealing as possible. They used well-trained salespeople and employees to maximize positive interactions and rescue negative ones. They carefully sequenced customer experiences, such as having a captain’s dinner on the final night of a cruise, to play on our hard-wired craving to end experiences on a high note.

sap Q217 digital double feature1 images1 Top Ten Digitalist Magazine Posts Of The Week [May 22, 2017]

Today, though, customer interactions are increasingly moving online. Fortune reports that on 2016’s Black Friday, the day after Thanksgiving that is so crucial to holiday retail results, 108.5 million Americans shopped online, while only 99.1 million visited brick-and-mortar stores. The 9.4% gap between the two was a dramatic change from just one year prior, when on- and offline Black Friday shopping were more or less equal.

When people browse in a store for a few minutes, an astute salesperson can read the telltale signs that they’re losing interest and heading for the exit. The salesperson can then intervene, answering questions and closing the sale.

Replicating that in a digital environment isn’t as easy, however. Despite all the investments companies have made to counteract e-shopping cart abandonment, they lack the data that would let them anticipate when a shopper is on the verge of opting out of a transaction, and the actions they take to lure someone back afterwards can easily come across as less helpful than intrusive.

In a digital environment, companies need to figure out how to use Big Data analysis and digital design to compensate for the absence of persuasive human communication and physical sights, sounds, and sensations. What’s more, a 2014 Gartner survey found that 89% of marketers expected customer experience to be their primary differentiator by 2016, and we’re already well into 2017.

As transactions continue to shift toward the digital and omnichannel, companies need to figure out new ways to gently push customers along the customer journey—and to do so without frustrating, offending, or otherwise alienating them.

sap Q217 digital double feature1 images6 1024x572 Top Ten Digitalist Magazine Posts Of The Week [May 22, 2017]

The quest to understand online customers better in order to influence them more effectively is built on a decades-old foundation: behavioral psychology, the study of the connections between what people believe and what they actually do. All of marketing and advertising is based on changing people’s thoughts in order to influence their actions. However, it wasn’t until 2001 that a now-famous article in the Harvard Business Review formally introduced the idea of applying behavioral psychology to customer service in particular.

The article’s authors, Richard B. Chase and Sriram Dasu, respectively a professor and assistant professor at the University of Southern California’s Marshall School of Business, describe how companies could apply fundamental tenets of behavioral psychology research to “optimize those extraordinarily important moments when the company touches its customers—for better and for worse.” Their five main points were simple but have proven effective across multiple industries:

  1. Finish strong. People evaluate experiences after the fact based on their high points and their endings, so the way a transaction ends is more important than how it begins.
  2. Front-load the negatives. To ensure a strong positive finish, get bad experiences out of the way early.
  3. Spread out the positives. Break up the pleasurable experiences into segments so they seem to last longer.
  4. Provide choices. People don’t like to be shoved toward an outcome; they prefer to feel in control. Giving them options within the boundaries of your ability to deliver builds their commitment.
  5. Be consistent. People like routine and predictability.

For example, McKinsey cites a major health insurance company that experimented with this framework in 2009 as part of its health management program. A test group of patients received regular coaching phone calls from nurses to help them meet health goals.

The front-loaded negative was inherent: the patients knew they had health problems that needed ongoing intervention, such as weight control or consistent use of medication. Nurses called each patient on a frequent, regular schedule to check their progress (consistency and spread-out positives), suggested next steps to keep them on track (choices), and cheered on their improvements (a strong finish).

McKinsey reports the patients in the test group were more satisfied with the health management program by seven percentage points, more satisfied with the insurance company by eight percentage points, and more likely to say the program motivated them to change their behavior by five percentage points.

sap Q217 digital double feature1 images2 Top Ten Digitalist Magazine Posts Of The Week [May 22, 2017]

The nurses who worked with the test group also reported increased job satisfaction. And these improvements all appeared in the first two weeks of the pilot program, without significantly affecting the company’s costs or tweaking key metrics, like the number and length of the calls.

Indeed, an ongoing body of research shows that positive reinforcements and indirect suggestions influence our decisions better and more subtly than blatant demands. This concept hit popular culture in 2008 with the bestselling book Nudge.

Written by University of Chicago economics professor Richard H. Thaler and Harvard Law School professor Cass R. Sunstein, Nudge first explains this principle, then explores it as a way to help people make decisions in their best interests, such as encouraging people to eat healthier by displaying fruits and vegetables at eye level or combatting credit card debt by placing a prominent notice on every credit card statement informing cardholders how much more they’ll spend over a year if they make only the minimum payment.

Whether they’re altruistic or commercial, nudges work because our decision-making is irrational in a predictable way. The question is how to apply that awareness to the digital economy.

sap Q217 digital double feature1 images7 1024x572 Top Ten Digitalist Magazine Posts Of The Week [May 22, 2017]

In its early days, digital marketing assumed that online shopping would be purely rational, a tool that customers would use to help them zero in on the best product at the best price. The assumption was logical, but customer behavior remained irrational.

Our society is overloaded with information and short on time, says Brad Berens, Senior Fellow at the Center for the Digital Future at the University of Southern California, Annenberg, so it’s no surprise that the speed of the digital economy exacerbates our desire to make a fast decision rather than a perfect one, as well as increasing our tendency to make choices based on impulse rather than logic.

sap Q217 digital double feature1 images3 Top Ten Digitalist Magazine Posts Of The Week [May 22, 2017]

Buyers want what they want, but they don’t necessarily understand or care why they want it. They just want to get it and move on, with minimal friction, to the next thing. “Most of our decisions aren’t very important, and we only have so much time to interrogate and analyze them,” Berens points out.

But limited time and mental capacity for decision-making is only half the issue. The other half is that while our brains are both logical and emotional, the emotional side—also known as the limbic system or, more casually, the primitive lizard brain—is far older and more developed. It’s strong enough to override logic and drive our decisions, leaving rational thought to, well, rationalize our choices after the fact.

This is as true in the B2B realm as it is for consumers. The business purchasing process, governed as it is by requests for proposals, structured procurement processes, and permission gating, is designed to ensure that the people with spending authority make the most sensible deals possible. However, research shows that even in this supposedly rational process, the relationship with the seller is still more influential than product quality in driving customer commitment and loyalty.

sap Q217 digital double feature1 images8 1024x572 Top Ten Digitalist Magazine Posts Of The Week [May 22, 2017]

Baba Shiv, a professor of marketing at Stanford University’s Graduate School of Business, studies how the emotional brain shapes decisions and experiences. In a popular TED Talk, he says that people in the process of making decisions fall into one of two mindsets: Type 1, which is stressed and wants to feel comforted and safe, and Type 2, which is bored or eager and wants to explore and take action.

People can move between these two mindsets, he says, but in both cases, the emotional brain is in control. Influencing it means first delivering a message that soothes or motivates, depending on the mindset the person happens to be in at the moment and only then presenting the logical argument to help rationalize the action.

In the digital economy, working with those tendencies means designing digital experiences with the full awareness that people will not evaluate them objectively, says Ravi Dhar, director of the Center for Customer Insights at the Yale School of Management. Since any experience’s greatest subjective impact in retrospect depends on what happens at the beginning, the end, and the peaks in between, companies need to design digital experiences to optimize those moments—to rationally design experiences for limited rationality.

This often involves making multiple small changes in the way options are presented well before the final nudge into making a purchase. A paper that Dhar co-authored for McKinsey offers the example of a media company that puts most of its content behind a paywall but offers free access to a limited number of articles a month as an incentive to drive subscriptions.

Many nonsubscribers reached their limit of free articles in the morning, but they were least likely to respond to a subscription offer generated by the paywall at that hour, because they were reading just before rushing out the door for the day. When the company delayed offers until later in the day, when readers were less distracted, successful subscription conversions increased.

Pre-selecting default options for necessary choices is another way companies can design digital experiences to follow customers’ preference for the path of least resistance. “We know from a decade of research that…defaults are a de facto nudge,” Dhar says.

For example, many online retailers set a default shipping option because customers have to choose a way to receive their packages and are more likely to passively allow the default option than actively choose another one. Similarly, he says, customers are more likely to enroll in a program when the default choice is set to accept it rather than to opt out.

Another intriguing possibility lies in the way customers react differently to on-screen information based on how that information is presented. Even minor tweaks can have a disproportionate impact on the choices people make, as explained in depth by University of California, Los Angeles, behavioral economist Shlomo Benartzi in his 2015 book, The Smarter Screen.

A few of the conclusions Benartzi reached: items at the center of a laptop screen draw more attention than those at the edges. Those on the upper left of a screen split into quadrants attract more attention than those on the lower left. And intriguingly, demographics are important variables.

Benartzi cites research showing that people over 40 prefer more visually complicated, text-heavy screens than younger people, who are drawn to saturated colors and large images. Women like screens that use a lot of different colors, including pastels, while men prefer primary colors on a grey or white background. People in Malaysia like lots of color; people in Germany don’t.

This suggests companies need to design their online experiences very differently for middle-aged women than they do for teenage boys. And, as Benartzi writes, “it’s easy to imagine a future in which each Internet user has his or her own ‘aesthetic algorithm,’ customizing the appearance of every site they see.”

Applying behavioral psychology to the digital experience in more sophisticated ways will require additional formal research into recommendation algorithms, predictions, and other applications of customer data science, says Jim Guszcza, PhD, chief U.S. data scientist for Deloitte Consulting.

In fact, given customers’ tendency to make the fastest decisions, Guszcza believes that in some cases, companies may want to consider making choice environments more difficult to navigate— a process he calls “disfluencing”—in high-stakes situations, like making an important medical decision or an irreversible big-ticket purchase. Choosing a harder-to-read font and a layout that requires more time to navigate forces customers to work harder to process the information, sending a subtle signal that it deserves their close attention.

That said, a company can’t apply behavioral psychology to deliver a digital experience if customers don’t engage with its site or mobile app in the first place. Addressing this often means making the process as convenient as possible, itself a behavioral nudge.

A digital solution that’s easy to use and search, offers a variety of choices pre-screened for relevance, and provides a friction-free transaction process is the equivalent of putting a product at eye level—and that applies far beyond retail. Consider the Global Entry program, which streamlines border crossings into the U.S. for pre-approved international travelers. Members can skip long passport control lines in favor of scanning their passports and answering a few questions at a touchscreen kiosk. To date, 1.8 million people have decided this convenience far outweighs the slow pace of approvals.

sap Q217 digital double feature1 images9 1024x572 Top Ten Digitalist Magazine Posts Of The Week [May 22, 2017]

The basics of influencing irrational customers are essentially the same whether they’re taking place in a store or on a screen. A business still needs to know who its customers are, understand their needs and motivations, and give them a reason to buy.

And despite the accelerating shift to digital commerce, we still live in a physical world. “There’s no divide between old-style analog retail and new-style digital retail,” Berens says. “Increasingly, the two are overlapping. One of the things we’ve seen for years is that people go into a store with their phones, shop for a better price, and buy online. Or vice versa: they shop online and then go to a store to negotiate for a better deal.”

Still, digital increases the number of touchpoints from which the business can gather, cluster, and filter more types of data to make great suggestions that delight and surprise customers. That’s why the hottest word in marketing today is omnichannel. Bringing behavioral psychology to bear on the right person in the right place in the right way at the right time requires companies to design customer experiences that bridge multiple channels, on- and offline.

Amazon, for example, is known for its friction-free online purchasing. The company’s pilot store in Seattle has no lines or checkout counters, extending the brand experience into the physical world in a way that aligns with what customers already expect of it, Dhar says.

Omnichannel helps counter some people’s tendency to believe their purchasing decision isn’t truly well informed unless they can see, touch, hear, and in some cases taste and smell a product. Until we have ubiquitous access to virtual reality systems with full haptic feedback, the best way to address these concerns is by providing personalized, timely, relevant information and feedback in the moment through whatever channel is appropriate. That could be an automated call center that answers frequently asked questions, a video that shows a product from every angle, or a demonstration wizard built into the product. Any of these channels could also suggest the customer visit the nearest store to receive help from a human.

sap Q217 digital double feature1 images4 Top Ten Digitalist Magazine Posts Of The Week [May 22, 2017]

The omnichannel approach gives businesses plenty of opportunities to apply subtle nudges across physical and digital channels. For example, a supermarket chain could use store-club card data to push personalized offers to customers’ smartphones while they shop. “If the data tells them that your goal is to feed a family while balancing nutrition and cost, they could send you an e-coupon offering a discount on a brand of breakfast cereal that tastes like what you usually buy but contains half the sugar,” Guszcza says.

Similarly, a car insurance company could provide periodic feedback to policyholders through an app or even the digital screens in their cars, he suggests. “Getting a warning that you’re more aggressive than 90% of comparable drivers and three tips to avoid risk and lower your rates would not only incentivize the driver to be more careful for financial reasons but reduce claims and make the road safer for everyone.”

Digital channels can also show shoppers what similar people or organizations are buying, let them solicit feedback from colleagues or friends, and read reviews from other people who have made the same purchases. This leverages one of the most familiar forms of behavioral psychology—reinforcement from peers—and reassures buyers with Shiv’s Type 1 mindset that they’re making a choice that meets their needs or encourages those with the Type 2 mindset to move forward with the purchase. The rational mind only has to ask at the end of the process “Am I getting the best deal?” And as Guszcza points out, “If you can create solutions that use behavioral design and digital technology to turn my personal data into insight to reach my goals, you’ve increased the value of your engagement with me so much that I might even be willing to pay you more.”

sap Q217 digital double feature1 images10 1024x572 Top Ten Digitalist Magazine Posts Of The Week [May 22, 2017]

Many transactions take place through corporate procurement systems that allow a company to leverage not just its own purchasing patterns but all the data in a marketplace specifically designed to facilitate enterprise purchasing. Machine learning can leverage this vast database of information to provide the necessary nudge to optimize purchasing patterns, when to buy, how best to negotiate, and more. To some extent, this is an attempt to eliminate psychology and make choices more rational.

B2B spending is tied into financial systems and processes, logistics systems, transportation systems, and other operational requirements in a way no consumer spending can be. A B2B decision is less about making a purchase that satisfies a desire than it is about making a purchase that keeps the company functioning.

That said, the decision still isn’t entirely rational, Berens says. When organizations have to choose among vendors offering relatively similar products and services, they generally opt for the vendor whose salespeople they like the best.

This means B2B companies have to make sure they meet or exceed parity with competitors on product quality, pricing, and time to delivery to satisfy all the rational requirements of the decision process. Only then can they bring behavioral psychology to bear by delivering consistently superior customer service, starting as soon as the customer hits their app or website and spreading out positive interactions all the way through post-purchase support. Finishing strong with a satisfied customer reinforces the relationship with a business customer just as much as it does with a consumer.

sap Q217 digital double feature1 images11 1024x572 Top Ten Digitalist Magazine Posts Of The Week [May 22, 2017]

The best nudges make the customer relationship easy and enjoyable by providing experiences that are effortless and fun to choose, on- or offline, Dhar says. What sets the digital nudge apart in accommodating irrational customers is its ability to turn data about them and their journey into more effective, personalized persuasion even in the absence of the human touch.

Yet the subtle art of influencing customers isn’t just about making a sale, and it certainly shouldn’t be about persuading people to act against their own best interests, as Nudge co-author Thaler reminds audiences by exhorting them to “nudge for good.”

Guszcza, who talks about influencing people to make the choices they would make if only they had unlimited rationality, says companies that leverage behavioral psychology in their digital experiences should do so with an eye to creating positive impact for the customer, the company, and, where appropriate, the society.

In keeping with that ethos, any customer experience designed along behavioral lines has to include the option of letting the customer make a different choice, such as presenting a confirmation screen at the end of the purchase process with the cold, hard numbers and letting them opt out of the transaction altogether.

“A nudge is directing people in a certain direction,” Dhar says. “But for an ethical vendor, the only right direction to nudge is the right direction as judged by the customers themselves.” D!

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.


About the Authors:

Volker Hildebrand is Global Vice President for SAP Hybris solutions.

Sam Yen is Chief Design Officer and Managing Director at SAP.

Fawn Fitter is a freelance writer specializing in business and technology.

Comments

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Digitalist Magazine

Real-Time Payments Should Be Widely Available By Mid-2018

When it comes to buying things—even big-ticket items—the way we make decisions makes no sense. One person makes an impulsive offer on a house because of the way the light comes in through the kitchen windows. Another gleefully drives a high-end sports car off the lot even though it will probably never approach the limits it was designed to push.

We can (and usually do) rationalize these decisions after the fact by talking about needing more closet space or wanting to out-accelerate an 18-wheeler as we merge onto the highway, but years of study have arrived at a clear conclusion:

When it comes to the customer experience, human beings are fundamentally irrational.

In the brick-and-mortar past, companies could leverage that irrationality in time-tested ways. They relied heavily on physical context, such as an inviting retail space, to make products and services as psychologically appealing as possible. They used well-trained salespeople and employees to maximize positive interactions and rescue negative ones. They carefully sequenced customer experiences, such as having a captain’s dinner on the final night of a cruise, to play on our hard-wired craving to end experiences on a high note.

sap Q217 digital double feature1 images1 Real Time Payments Should Be Widely Available By Mid 2018

Today, though, customer interactions are increasingly moving online. Fortune reports that on 2016’s Black Friday, the day after Thanksgiving that is so crucial to holiday retail results, 108.5 million Americans shopped online, while only 99.1 million visited brick-and-mortar stores. The 9.4% gap between the two was a dramatic change from just one year prior, when on- and offline Black Friday shopping were more or less equal.

When people browse in a store for a few minutes, an astute salesperson can read the telltale signs that they’re losing interest and heading for the exit. The salesperson can then intervene, answering questions and closing the sale.

Replicating that in a digital environment isn’t as easy, however. Despite all the investments companies have made to counteract e-shopping cart abandonment, they lack the data that would let them anticipate when a shopper is on the verge of opting out of a transaction, and the actions they take to lure someone back afterwards can easily come across as less helpful than intrusive.

In a digital environment, companies need to figure out how to use Big Data analysis and digital design to compensate for the absence of persuasive human communication and physical sights, sounds, and sensations. What’s more, a 2014 Gartner survey found that 89% of marketers expected customer experience to be their primary differentiator by 2016, and we’re already well into 2017.

As transactions continue to shift toward the digital and omnichannel, companies need to figure out new ways to gently push customers along the customer journey—and to do so without frustrating, offending, or otherwise alienating them.

sap Q217 digital double feature1 images6 1024x572 Real Time Payments Should Be Widely Available By Mid 2018

The quest to understand online customers better in order to influence them more effectively is built on a decades-old foundation: behavioral psychology, the study of the connections between what people believe and what they actually do. All of marketing and advertising is based on changing people’s thoughts in order to influence their actions. However, it wasn’t until 2001 that a now-famous article in the Harvard Business Review formally introduced the idea of applying behavioral psychology to customer service in particular.

The article’s authors, Richard B. Chase and Sriram Dasu, respectively a professor and assistant professor at the University of Southern California’s Marshall School of Business, describe how companies could apply fundamental tenets of behavioral psychology research to “optimize those extraordinarily important moments when the company touches its customers—for better and for worse.” Their five main points were simple but have proven effective across multiple industries:

  1. Finish strong. People evaluate experiences after the fact based on their high points and their endings, so the way a transaction ends is more important than how it begins.
  2. Front-load the negatives. To ensure a strong positive finish, get bad experiences out of the way early.
  3. Spread out the positives. Break up the pleasurable experiences into segments so they seem to last longer.
  4. Provide choices. People don’t like to be shoved toward an outcome; they prefer to feel in control. Giving them options within the boundaries of your ability to deliver builds their commitment.
  5. Be consistent. People like routine and predictability.

For example, McKinsey cites a major health insurance company that experimented with this framework in 2009 as part of its health management program. A test group of patients received regular coaching phone calls from nurses to help them meet health goals.

The front-loaded negative was inherent: the patients knew they had health problems that needed ongoing intervention, such as weight control or consistent use of medication. Nurses called each patient on a frequent, regular schedule to check their progress (consistency and spread-out positives), suggested next steps to keep them on track (choices), and cheered on their improvements (a strong finish).

McKinsey reports the patients in the test group were more satisfied with the health management program by seven percentage points, more satisfied with the insurance company by eight percentage points, and more likely to say the program motivated them to change their behavior by five percentage points.

sap Q217 digital double feature1 images2 Real Time Payments Should Be Widely Available By Mid 2018

The nurses who worked with the test group also reported increased job satisfaction. And these improvements all appeared in the first two weeks of the pilot program, without significantly affecting the company’s costs or tweaking key metrics, like the number and length of the calls.

Indeed, an ongoing body of research shows that positive reinforcements and indirect suggestions influence our decisions better and more subtly than blatant demands. This concept hit popular culture in 2008 with the bestselling book Nudge.

Written by University of Chicago economics professor Richard H. Thaler and Harvard Law School professor Cass R. Sunstein, Nudge first explains this principle, then explores it as a way to help people make decisions in their best interests, such as encouraging people to eat healthier by displaying fruits and vegetables at eye level or combatting credit card debt by placing a prominent notice on every credit card statement informing cardholders how much more they’ll spend over a year if they make only the minimum payment.

Whether they’re altruistic or commercial, nudges work because our decision-making is irrational in a predictable way. The question is how to apply that awareness to the digital economy.

sap Q217 digital double feature1 images7 1024x572 Real Time Payments Should Be Widely Available By Mid 2018

In its early days, digital marketing assumed that online shopping would be purely rational, a tool that customers would use to help them zero in on the best product at the best price. The assumption was logical, but customer behavior remained irrational.

Our society is overloaded with information and short on time, says Brad Berens, Senior Fellow at the Center for the Digital Future at the University of Southern California, Annenberg, so it’s no surprise that the speed of the digital economy exacerbates our desire to make a fast decision rather than a perfect one, as well as increasing our tendency to make choices based on impulse rather than logic.

sap Q217 digital double feature1 images3 Real Time Payments Should Be Widely Available By Mid 2018

Buyers want what they want, but they don’t necessarily understand or care why they want it. They just want to get it and move on, with minimal friction, to the next thing. “Most of our decisions aren’t very important, and we only have so much time to interrogate and analyze them,” Berens points out.

But limited time and mental capacity for decision-making is only half the issue. The other half is that while our brains are both logical and emotional, the emotional side—also known as the limbic system or, more casually, the primitive lizard brain—is far older and more developed. It’s strong enough to override logic and drive our decisions, leaving rational thought to, well, rationalize our choices after the fact.

This is as true in the B2B realm as it is for consumers. The business purchasing process, governed as it is by requests for proposals, structured procurement processes, and permission gating, is designed to ensure that the people with spending authority make the most sensible deals possible. However, research shows that even in this supposedly rational process, the relationship with the seller is still more influential than product quality in driving customer commitment and loyalty.

sap Q217 digital double feature1 images8 1024x572 Real Time Payments Should Be Widely Available By Mid 2018

Baba Shiv, a professor of marketing at Stanford University’s Graduate School of Business, studies how the emotional brain shapes decisions and experiences. In a popular TED Talk, he says that people in the process of making decisions fall into one of two mindsets: Type 1, which is stressed and wants to feel comforted and safe, and Type 2, which is bored or eager and wants to explore and take action.

People can move between these two mindsets, he says, but in both cases, the emotional brain is in control. Influencing it means first delivering a message that soothes or motivates, depending on the mindset the person happens to be in at the moment and only then presenting the logical argument to help rationalize the action.

In the digital economy, working with those tendencies means designing digital experiences with the full awareness that people will not evaluate them objectively, says Ravi Dhar, director of the Center for Customer Insights at the Yale School of Management. Since any experience’s greatest subjective impact in retrospect depends on what happens at the beginning, the end, and the peaks in between, companies need to design digital experiences to optimize those moments—to rationally design experiences for limited rationality.

This often involves making multiple small changes in the way options are presented well before the final nudge into making a purchase. A paper that Dhar co-authored for McKinsey offers the example of a media company that puts most of its content behind a paywall but offers free access to a limited number of articles a month as an incentive to drive subscriptions.

Many nonsubscribers reached their limit of free articles in the morning, but they were least likely to respond to a subscription offer generated by the paywall at that hour, because they were reading just before rushing out the door for the day. When the company delayed offers until later in the day, when readers were less distracted, successful subscription conversions increased.

Pre-selecting default options for necessary choices is another way companies can design digital experiences to follow customers’ preference for the path of least resistance. “We know from a decade of research that…defaults are a de facto nudge,” Dhar says.

For example, many online retailers set a default shipping option because customers have to choose a way to receive their packages and are more likely to passively allow the default option than actively choose another one. Similarly, he says, customers are more likely to enroll in a program when the default choice is set to accept it rather than to opt out.

Another intriguing possibility lies in the way customers react differently to on-screen information based on how that information is presented. Even minor tweaks can have a disproportionate impact on the choices people make, as explained in depth by University of California, Los Angeles, behavioral economist Shlomo Benartzi in his 2015 book, The Smarter Screen.

A few of the conclusions Benartzi reached: items at the center of a laptop screen draw more attention than those at the edges. Those on the upper left of a screen split into quadrants attract more attention than those on the lower left. And intriguingly, demographics are important variables.

Benartzi cites research showing that people over 40 prefer more visually complicated, text-heavy screens than younger people, who are drawn to saturated colors and large images. Women like screens that use a lot of different colors, including pastels, while men prefer primary colors on a grey or white background. People in Malaysia like lots of color; people in Germany don’t.

This suggests companies need to design their online experiences very differently for middle-aged women than they do for teenage boys. And, as Benartzi writes, “it’s easy to imagine a future in which each Internet user has his or her own ‘aesthetic algorithm,’ customizing the appearance of every site they see.”

Applying behavioral psychology to the digital experience in more sophisticated ways will require additional formal research into recommendation algorithms, predictions, and other applications of customer data science, says Jim Guszcza, PhD, chief U.S. data scientist for Deloitte Consulting.

In fact, given customers’ tendency to make the fastest decisions, Guszcza believes that in some cases, companies may want to consider making choice environments more difficult to navigate— a process he calls “disfluencing”—in high-stakes situations, like making an important medical decision or an irreversible big-ticket purchase. Choosing a harder-to-read font and a layout that requires more time to navigate forces customers to work harder to process the information, sending a subtle signal that it deserves their close attention.

That said, a company can’t apply behavioral psychology to deliver a digital experience if customers don’t engage with its site or mobile app in the first place. Addressing this often means making the process as convenient as possible, itself a behavioral nudge.

A digital solution that’s easy to use and search, offers a variety of choices pre-screened for relevance, and provides a friction-free transaction process is the equivalent of putting a product at eye level—and that applies far beyond retail. Consider the Global Entry program, which streamlines border crossings into the U.S. for pre-approved international travelers. Members can skip long passport control lines in favor of scanning their passports and answering a few questions at a touchscreen kiosk. To date, 1.8 million people have decided this convenience far outweighs the slow pace of approvals.

sap Q217 digital double feature1 images9 1024x572 Real Time Payments Should Be Widely Available By Mid 2018

The basics of influencing irrational customers are essentially the same whether they’re taking place in a store or on a screen. A business still needs to know who its customers are, understand their needs and motivations, and give them a reason to buy.

And despite the accelerating shift to digital commerce, we still live in a physical world. “There’s no divide between old-style analog retail and new-style digital retail,” Berens says. “Increasingly, the two are overlapping. One of the things we’ve seen for years is that people go into a store with their phones, shop for a better price, and buy online. Or vice versa: they shop online and then go to a store to negotiate for a better deal.”

Still, digital increases the number of touchpoints from which the business can gather, cluster, and filter more types of data to make great suggestions that delight and surprise customers. That’s why the hottest word in marketing today is omnichannel. Bringing behavioral psychology to bear on the right person in the right place in the right way at the right time requires companies to design customer experiences that bridge multiple channels, on- and offline.

Amazon, for example, is known for its friction-free online purchasing. The company’s pilot store in Seattle has no lines or checkout counters, extending the brand experience into the physical world in a way that aligns with what customers already expect of it, Dhar says.

Omnichannel helps counter some people’s tendency to believe their purchasing decision isn’t truly well informed unless they can see, touch, hear, and in some cases taste and smell a product. Until we have ubiquitous access to virtual reality systems with full haptic feedback, the best way to address these concerns is by providing personalized, timely, relevant information and feedback in the moment through whatever channel is appropriate. That could be an automated call center that answers frequently asked questions, a video that shows a product from every angle, or a demonstration wizard built into the product. Any of these channels could also suggest the customer visit the nearest store to receive help from a human.

sap Q217 digital double feature1 images4 Real Time Payments Should Be Widely Available By Mid 2018

The omnichannel approach gives businesses plenty of opportunities to apply subtle nudges across physical and digital channels. For example, a supermarket chain could use store-club card data to push personalized offers to customers’ smartphones while they shop. “If the data tells them that your goal is to feed a family while balancing nutrition and cost, they could send you an e-coupon offering a discount on a brand of breakfast cereal that tastes like what you usually buy but contains half the sugar,” Guszcza says.

Similarly, a car insurance company could provide periodic feedback to policyholders through an app or even the digital screens in their cars, he suggests. “Getting a warning that you’re more aggressive than 90% of comparable drivers and three tips to avoid risk and lower your rates would not only incentivize the driver to be more careful for financial reasons but reduce claims and make the road safer for everyone.”

Digital channels can also show shoppers what similar people or organizations are buying, let them solicit feedback from colleagues or friends, and read reviews from other people who have made the same purchases. This leverages one of the most familiar forms of behavioral psychology—reinforcement from peers—and reassures buyers with Shiv’s Type 1 mindset that they’re making a choice that meets their needs or encourages those with the Type 2 mindset to move forward with the purchase. The rational mind only has to ask at the end of the process “Am I getting the best deal?” And as Guszcza points out, “If you can create solutions that use behavioral design and digital technology to turn my personal data into insight to reach my goals, you’ve increased the value of your engagement with me so much that I might even be willing to pay you more.”

sap Q217 digital double feature1 images10 1024x572 Real Time Payments Should Be Widely Available By Mid 2018

Many transactions take place through corporate procurement systems that allow a company to leverage not just its own purchasing patterns but all the data in a marketplace specifically designed to facilitate enterprise purchasing. Machine learning can leverage this vast database of information to provide the necessary nudge to optimize purchasing patterns, when to buy, how best to negotiate, and more. To some extent, this is an attempt to eliminate psychology and make choices more rational.

B2B spending is tied into financial systems and processes, logistics systems, transportation systems, and other operational requirements in a way no consumer spending can be. A B2B decision is less about making a purchase that satisfies a desire than it is about making a purchase that keeps the company functioning.

That said, the decision still isn’t entirely rational, Berens says. When organizations have to choose among vendors offering relatively similar products and services, they generally opt for the vendor whose salespeople they like the best.

This means B2B companies have to make sure they meet or exceed parity with competitors on product quality, pricing, and time to delivery to satisfy all the rational requirements of the decision process. Only then can they bring behavioral psychology to bear by delivering consistently superior customer service, starting as soon as the customer hits their app or website and spreading out positive interactions all the way through post-purchase support. Finishing strong with a satisfied customer reinforces the relationship with a business customer just as much as it does with a consumer.

sap Q217 digital double feature1 images11 1024x572 Real Time Payments Should Be Widely Available By Mid 2018

The best nudges make the customer relationship easy and enjoyable by providing experiences that are effortless and fun to choose, on- or offline, Dhar says. What sets the digital nudge apart in accommodating irrational customers is its ability to turn data about them and their journey into more effective, personalized persuasion even in the absence of the human touch.

Yet the subtle art of influencing customers isn’t just about making a sale, and it certainly shouldn’t be about persuading people to act against their own best interests, as Nudge co-author Thaler reminds audiences by exhorting them to “nudge for good.”

Guszcza, who talks about influencing people to make the choices they would make if only they had unlimited rationality, says companies that leverage behavioral psychology in their digital experiences should do so with an eye to creating positive impact for the customer, the company, and, where appropriate, the society.

In keeping with that ethos, any customer experience designed along behavioral lines has to include the option of letting the customer make a different choice, such as presenting a confirmation screen at the end of the purchase process with the cold, hard numbers and letting them opt out of the transaction altogether.

“A nudge is directing people in a certain direction,” Dhar says. “But for an ethical vendor, the only right direction to nudge is the right direction as judged by the customers themselves.” D!

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.


About the Authors:

Volker Hildebrand is Global Vice President for SAP Hybris solutions.

Sam Yen is Chief Design Officer and Managing Director at SAP.

Fawn Fitter is a freelance writer specializing in business and technology.

Comments

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Digitalist Magazine

Cumulative Update #6 for SQL Server 2016 RTM

The 6th cumulative update release for SQL Server 2016 RTM is now available for download at the Microsoft Downloads site. Please note that registration is no longer required to download Cumulative updates.

To learn more about the release or servicing model, please visit:

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SQL Server Release Services

Adding text in images

My question is simple

How can I add text in a figure like the following?

M0KgZ Adding text in images

In particular I want two labels: one at the top “Label text 1″ ()just above the image and one at the right side (just outside), written vertically “Label text 2″. Of course, I must be able to control the font family, size, etc of the labels.

Any suggestions?

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Recent Questions – Mathematica Stack Exchange