March 2019 - Business Intelligence Info

Monthly Archives: March 2019

Using the Contact Center to Help Build Brand Loyalty

March 31, 2019 CRM News and Info

In 2018, 8.8 percent of all retail sales globally, totaling more than US$ 2 trillion, were made online, according to the
Global Online Retail Spending report. As the total number of online purchases continues to grow, a compelling case can be made that e-commerce customers expect to receive support that is as good as or even better than those who purchase the very same products in a store.

In person, it is very easy to verify the proper set-up and operation. A return or exchange is immediate, thereby ensuring any outstanding issues can be solved on-premises and in person. Contrast this experience with one involving a product delivered to a home or business. Without the agent being able to see the problem, the customer is forced to “paint a picture” with the proverbial 1,000-word description.

The challenge with e-commerce, therefore, is to find a way to deliver customer support with a personal touch and effectiveness similar to the in-store experience. To be sure, customer support via contact centers has improved over time, but legitimate complaints remain far too common.

Confusing interactive voice response (IVR) navigation regularly leads to multiple transfers before a customer reaches an agent who can resolve the issue. The need to repeat details over and over again while being passed around annoys customers and adds to agent workloads.

Then, just when the customer is finally going to be transferred to the right agent, the call gets dropped. Such experiences are frustrating at best and infuriating at worst, and they serve to undermine brand loyalty.

This article examines some advances being made — now and over the foreseeable future — in contact center operations. These advances not only improve customer satisfaction, but also enhance the productivity and job satisfaction of agents.

Customer Service Is Increasingly Data-Driven

The wealth of data available in customer relationship management (CRM) and other systems now makes it possible to elevate support experiences, strengthen brand appreciation, increase customer lifetime value (CLV), and help foster positive social media reach and impact. These and other improvements hold the potential to turn the contact center from being a cost center to becoming a strategic asset for building the brand in competitive markets.

The purpose-built customer support platforms enabling these improvements provide two significant advances that together make it possible to resolve issues better and faster than ever before. The first is the ability to tap the wealth of data currently available about customers, products, common questions, agent expertise, contact center activity and more. The second advance involves leveraging the data being provided by smart devices, especially smartphones.

Making pertinent data available during every customer support session should be considered the minimum capability needed to deliver effective, efficient and positive support experiences to customers.

The data should be presented to the agent in a meaningful and secure way at the very beginning of the call to ensure the fastest possible resolution. Done well, this data-driven approach eliminates the need to ask customers to repeat or re-enter information the company already has, and helps route each call to an agent who is able to resolve the issue quickly and efficiently.

Getting calls routed to the right queue the first time is enabled when the customer support platform is connected to external data sources to access customer profile or segmentation information stored in the CRM. This connection works two ways, of course, enabling the CRM to be updated with new information made available during the support call. These insights also give supervisors the visibility they need to optimize overall contact center operations.

Customer Support Platforms in the Cloud

The cloud makes it easy for organizations of any size to take advantage of state-of-the-art technologies, including Contact Center as a Service (CCaaS) solutions. For smaller organizations, the cloud provides a complete solution (hardware, software and support), thereby eliminating the need to hire and retain a staff of experts. For large organizations, the cloud’s virtually unlimited scalability is a significant advantage.

Cloud-based services are versatile, scalable and cost-effective, and easily can be updated to make new and enhanced capabilities available regularly. CCaaS offerings have all the advantages of the cloud, in general, and because they are purpose-built for the cloud, it’s easier to integrate them with other business systems and data sources.

For example, the CRM system could provide a customer’s purchase history and previous experiences with support. Or, an interface to a knowledge base could display a list of likely problems to customers, along with how to evaluate and resolve them.

Most of the cloud customer support platforms offer built-in interfaces or “connectors” that integrate with popular CRM, workforce management and other systems. However, even those commercial or custom applications that lack a pre-built connector can be integrated using published application programming interfaces (APIs) and software development kits (SDKs).

Smartphone-Enabled Customer Support

The second advance in customer support platforms is the ability to harness the full power and potential of the smartphone. Smartphones have revolutionized the conversational experience with their multimedia capabilities, and they continue to offer an evolving range of technical abilities and functionality.

Rather than force customers to use their smartphones just as phones, customer support platforms have made it possible to tap the phones’ other capabilities for sharing photos, video and texts to create a much richer and more streamlined support experience in many situations.

Such multimedia communications effectively turn the smartphone into the equivalent of a powerful customer service portal. Leveraging the smartphone’s ability to provide actionable data quickly and easily results in an enhanced conversational experience where customers no longer feel their time and effort is being wasted.

The potential is so great that some companies have integrated customer support capabilities into their existing mobile apps. From within the app, the customer could initiate a support session, and the app automatically would upload useful information to the customer support platform, where it would be made available to the agent.

The many sources of information include the app’s status, any user data available to the app, the most recent user actions in the app, diagnostic test results, device ID, operating system version, and the user’s location (via GPS). The app also could make it easy to access the smartphone’s many features and functions, including verifying the user’s identity with a fingerprint or facial scan.

Getting More Data From More Devices

With the cloud now extending into homes via devices like Amazon Echo, Google Home and Apple HomePod, users have an additional way to communicate, make purchases — and yes, handle support needs.

As these devices become more pervasive, companies will be motivated to consider enhancing their customer support capabilities with concierge communications. Voice communications will be fairly seamless, because voice is a native function of the device. However, the session could be made multimedia by incorporating the smartphone into the call to take advantage of its texting, imaging, video, user authentication and other functions.

The Internet of Things (IoT) has created even more opportunities to enhance the conversational experience. Many such devices gather data in real-time and make it available for historical or forensic purposes. Continuous monitoring makes it possible to detect a problem, issue an alert, and — as part of a proactive customer support offering — automatically initiate a session with the contact center. Imagine just how satisfied a customer would be when receiving a notification to fix a problem that the customer didn’t yet know had occurred.

Context-Awareness Maximizes Customer Service Satisfaction and Agent Productivity

Establishing an accurate and actionable context for all customer support sessions is a proven way to deliver a satisfactory contact center experience every time. Awareness of the customer’s context — for example, recent purchase and delivery history; previous product experiences; changes in user profile status, such as a new home address, known failure of a connected device, and more — puts the agent in a better position to anticipate and address the customer’s situation quickly and satisfactorily.

By contrast, the lack of meaningful context is the root cause of the all-too-common and particularly annoying complaints customers have about contact centers: needing to respond to too many questions about the current problem or situation, whether by navigating multiple levels of menu options or by talking with agents.

The objective of providing context is to make it easy for customers to get their issues resolved as quickly as possible. In many other interactions with companies, technological advances have simplified the way customers sign in or sign up, purchase goods or services, get information, or complete other actions.

Consider, for example, the ability to complete a purchase with a single click. With such user-friendliness now so familiar, customers may wonder why interactions with contact centers remain so cumbersome and frustrating.

Following are some examples of how the context provided by customer support platforms makes it easier for customers.

By reviewing each caller’s product purchase history and identifying any undelivered products, the customer immediately could be presented with an option to get shipping status. Or, the caller could be presented with a list of recent purchases to select the one with the problem, and then be presented with a list of common problems for that product.

If there were no self-service option available for the particular issue, the call then would be routed to an agent who could answer with something like this: “Hi John, I see you recently purchased a widget. Is that what you’re calling about? I’m sorry you’re having a problem setting it up. Let me help you with that.”

Proactive interactions put resolutions on a fast track, resulting in positive contact center experiences that increase customer satisfaction and brand loyalty. Making actionable contexts available to agents from the start eliminates the need for customers to explain their situation over and over again. With better insight into the customer’s situation and preferences, providing actionable contexts for agents can enhance and personalize the customer experience.

Resolving issues quickly on the first call has another advantage: It substantially increases agent productivity. A customer support platform can do even more to optimize overall contact center operations.

For example, a dashboard that provides supervisors with a real-time view of current call volume and agent activity affords opportunities to make adjustments during peak periods to avoid serious problems. Or, information about each agent’s performance, combined with recordings of actual calls, provides an opportunity for targeted coaching. It is worth noting that more productive agents often have higher levels of job satisfaction, which helps reduce turnover.

‘Intelligent Automation’ Will Further Enhance Contact Center Effectiveness

The potential for improvements in customer service with deep learning (DL), machine learning (ML) and artificial intelligence (AI) technologies currently is limited only by the imagination. While these terms increasingly are tossed around, often without a clear view of how they will be applied, the ultimate goal of each is what could be called “intelligent automation.”

In addition to improving contact center effectiveness, mainly through providing better context, these technologies present opportunities for improving self-service support options by more intelligently applying automation to guide users to the fastest-possible resolution to common problems.

Such improvements in automated support services minimize the need for agents to deal with mundane matters, freeing them to focus on the more challenging issues, VIP customers, and strategic scenarios where a personal touch is often necessary.

Successful use of intelligent automation can empower customers to handle common tasks themselves, more quickly and efficiently. For example, being directed to the correct self-service option, which provides easy-to-follow instructions, can delight just as much, if not more, than a similar experience with an agent.

Combining the power of the smartphone with the potential of intelligent automation affords virtually unlimited opportunities for enhancing contact center interactions. Some examples:

Using a combination of natural language processing and AI to automatically present the most appropriate knowledge base information to agents during a live session;
Using AI pattern matching to identify and offer the most likely solutions to active inquiries in real time;
Increasing the use of self-service by directing callers to easy ways to complete common transactions on their smartphones, such as changing contact information or tracking a shipment;
Using DL in the background during all customer interactions to extend self-service range and accuracy;
Automatically integrating the use of texting, videos, images or other smartphone functions;
Continuing the conversation using a live chat on the website where the customer and agent can interact simultaneously on their respective browsers.

ML and AI pattern matching also can be used to fine-tune customer segmentation, including updating probabilities of a specific customer encountering a particular problem. This form of intelligent automation can be used either for enhancing context to present more meaningful options during inbound sessions, or for proactive initiation of outbound notifications with directions to a convenient self-serve solution.

Eventually, intelligent automation will go beyond the chatbot to create what could be called the “artificial agent.” For example, a flight gets canceled, and all passengers receive calls offering them a choice of options for booking another flight.

Most may want to choose a self-serve option where they are presented with a list of available flights on their smartphone’s browser. Others may need to speak with an artificial or actual agent because they are currently driving to the airport. Either way, combining the intelligent automation of a customer support platform with the power of a smartphone makes for a promising future for contact centers.

Getting Started

Continuing to treat the contact center as a cost center is costing companies money. Using a customer support platform that improves the effectiveness of contact centers pays for itself — and more — in two ways. The first is through an increase in customer satisfaction and brand loyalty, which lead to reduced customer churn and higher customer lifetime values. The second is through cost reductions via increased agent productivity, the potential to minimize call transfers, and the economies of scale afforded by Contact Center as a Service offerings.

These and other potential improvements have motivated more companies to transform their contact centers from a cost center to a strategic asset capable of creating a competitive advantage.

For those companies unwilling to make this change at this time, consider this: As companies begin to leverage customer data to enhance and streamline the support experience, customers will start to expect it, and they will become increasingly frustrated with companies that don’t take advantage of the data they have.

Get started by evaluating current contact center operations to uncover areas for improvement. The assessment should look for gaps in existing processes and determine how best to close those gaps, either with existing practices and technologies or new ones. While doing so, evaluate all current systems for how capable and extensible they are, and investigate available options for making enhancements.

For example, can your existing systems effectively utilize available data to provide meaningful context, or leverage the feature-rich power of smartphones? If not, your current systems are limiting your ability to deliver world-class customer support. Finally, estimate how the various improvements might increase customer satisfaction — and revenue.

At a minimum, identify at least one aspect of the customer support experience you can improve now, along with one area of agent workload you can reduce. You might be surprised at just how easy it is to begin adopting a data-driven, contextual approach to customer support.

Joerg Habermeier is head of product at
UJET, where his focus is on providing an ultra-modern customer support solution via a flexible SaaS platform. Joerg has more than 20 years experience directing, designing, implementing, and launching products and features for companies such as Facebook, Pypestream and StrongView. He holds a masters of environmental science and management from Yale University and a masters of water resources systems engineering from Tufts University.

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Driving Change In Utilities – It’s Not Just A Pipe Dream

March 31, 2019 BI News and Info

2019 is well underway – the hairs are getting greyer, Fortnite continues to extract every last penny of my kids’ pocket money, and the utilities industry here in the UK appears to be thriving.

Now, I can explain the first of these. The second baffles me, and the third is testimony and credit to the people driving change within the industry.

I’ve been lucky enough to work with some of the key utilities organisations here in the UK. Over the past three years, I’ve been involved in leading or assuring a number of high-profile enterprise-wide business transformations that have either led or placed significant focus on a business change element, with the backbone of these transformations being technology.

Technology is by no means the single driver. I’ve been working hard to understand the established complex business models in energy, how these companies are changing (and moreover, what is driving this change), the disruptive new players who are entering the market, and the new technologies that are gradually reaching scalability, resilience, and greater adoption.

“Change” is, in my mind, the new trendy business term. Akin to the days when every half-reputable service provider or software solution glorified the likes of “service-oriented architecture”, “change” and its seemingly intertwined twins, “innovation” and “transformation”, is the new panacea that everyone promises – yet often fails to deliver.

To look at what change means for utilities companies, I wanted to take it back to the business drivers. I believe that 2019 is likely to present organisations with a number of challenges. I see the challenges broken down into four key areas:

Affordability – Delivery of cost-effective supply which is commercially viable (under the watch of the regulator)
Service – Changes in customer expectations
Sustainability – Shifting patterns of use, demographics, population growth, and reduced reliance on traditional fossil fuels
Supply – Safety and reliability

The organisations I see that successfully deliver this technology-led change and address these challenges do it by focusing on the following areas:

Affordability – Standardising business processes, improving regulatory compliance, minimizing regret spend, and eliminate wasted investment. This leads to a simplified architecture and landscape, reducing storage, hosting, and running costs
Service – Making better use of software and reducing manual processes, allowing the workforce to re-focus on looking forward with real-time information, resulting in demonstrable improvement in customer service
Sustainability – Enabling the “living” network. Assets trigger their own maintenance work orders, pipes tell us where there is an ingress of water, pressure controls automatically adjust in real time. IoT solutions drive sustainability improvements
Supply – Transforming the ways in which they work with their assets and the data those assets generate. Mobile apps support digitisation of previously manual and paper-based processes in the field, feeding into the cloud. For example, gas distribution organisations predict gas leaks and the impacts on supply from local/regional demand

I would like to think that wherever utilities organisations are on their journey, we have at the very least listened and sought to understand the causes for, and impacts of, such change and how technology may help aid these.

Want to learn more about how AgilityWorks has addressed the challenges in a host of UK utilities companies? Get in touch.

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more Trump wrestling rhetoric as his insults wear thin

March 31, 2019 Humor

Because of Devin Nunes suing his mother and a cow on Twitter, Trump thought he could offset that bit of stupidity with a stunt involving Adam Schiff, to augment the House Intelligence committee Republicans’ attempt to oust him. Trump’s been workshopping nasty nicknames, but seems to reveal his own limited lexicon.

Trump chose to reduce his rhetoric to that of a professional wrestling spectacle, since that is the operative model for his campaign rallies. It also demonstrates that the Trump base ultimately devolves to the dynamics of pro-wrestling audiences.

“Pencil-neck” as in “pencil-neck geek” was a common expression used in Trump’s heyday appearing on WWE broadcasts. Wrestlers would refer to non-wrestlers as “pencil-necks”.

This bit of GOP humor is derived from the company of the former cabinet member for the Small Business Administration. Linda McMahon was even part of the ongoing kayfabe of WWE wrestling spectacles, as was Individual-1, a member of the WWE Hall of Fame.

President Trump‘s 2020 presidential campaign is now selling “Pencil-Neck Adam Schiff” T-shirts, after Trump coined the new nickname at a rally in Michigan on Thursday.

The shirt, which is on sale for $ 28, shows Rep. Adam Schiff (D-Calif.) with a pencil for a neck as well as a clown nose.

“Little Pencil-Neck Adam Schiff. He spent two years knowingly and unlawfully lying and leaking. He should be forced to resign from Congress! Everyone should buy a Pencil-Neck Adam Schiff shirt today!” the item’s online description reads.

thehill.com/…

Trump is running out of snappy insults as he tries something retro, as if the kids would understand.

The colorful phrase first started being used to mean “weak” in the 19th century but was popularized in the 20th century thanks to an unusual figure: wrestler “Classy” Freddie Blassie.

The famous wrestling villain from the 1960s and 1970s adopted the description as part of his signature catchphrase “pencil-neck geek” early in his career, when his rival was a wrestler known as “The Geek.” Blassie even later turned it into a novelty song.

It’s no secret that Trump has long had an affection for professional wrestling. World Wrestling Entertainment Inc., for example, inducted Trump into its Hall of Fame in 2013 for his contribution to the industry, as Trump has had a media relationship with the company since the inception of “Hulkamania” in the 1980s. Trump has even made some appearances as a guest wrestler, taking on others in the ring in full suit and tie.

zenith.news/…

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Key Tips for Scaling Your Startup from Jason Calacanis

March 31, 2019 NetSuite

Posted by Anthony Stames, Software Industry Marketing Lead

LAUNCH founder Jason Calacanis recently sat down with NetSuite to share what he’s learned over a career in which he’s invested in more than 200 startups, including unicorns like Uber, Thumbtack, Calm.com and Robinhood. Some of his insights are surprisingly counterintuitive, others refreshingly down-to-earth. They’re all expressed in the kind of frank, practical terms that the industry has come to expect from one of its boldest voices.

In the webinar, Calacanis explained what works in the earliest stages of a startup’s existence doesn’t necessarily attract angel investors; what an angel investor sees as a sign of promise might strike a venture capitalist considering a round of Series B financing as a threat to ROI or a negligent investment altogether. Businesses in the startup phase that anticipate these challenges make the best possible case for the kind of financing that drives increased market penetration and valuation.

Here are a few takeaways:

Generate Revenue Right Off the Bat

Calacanis’ first point is the most important: startups should have one business model, and it should include revenue generation from day one. A long-term vision of success is what gets startups off the ground, but Calacanis warns against applying that same long-term thinking to a startup’s business model.

The days are gone when most startups could count on slowly developing a user base before introducing advertising revenue: companies like Uber and Airbnb incorporated revenue generation into their earliest business models and adjusted their revenue streams only as they made commensurate changes to their services and overall business models. In time, a startup may produce strong, reliable revenue streams through subscriptions, advertising and affiliate programs, but it’s unlikely to get anywhere near that point if its founders don’t concentrate on what works best right from the start.

Avoid the Feature Death March

If a startup’s business model should stay simple, so should its approach to product development. Founders are naturally filled with ideas for their flagship products, some of which can be incorporated in beta, others of which need to be held for future releases. And the ideas keep coming as a startup matures. That’s a good thing…right?

Not always. Calacanis notes that most successful startups focus on steady, incremental improvements to core services, not the introduction of flashy new features. A startup’s goal should be to produce deep products and services of narrow scope; this approach tends to set a startup apart from its competition and to cultivate customer loyalty. Developers, who know this phenomenon as Feature Creep, will be happier, too.

Adjust Your Team

It’s an awkward and often painful reality, but the right team for a startup’s bootstrapping phase isn’t the right one for an angel investor. Founding partners who feel right at home in the whack-a-mole flurry of a startup’s early days may not be content with just one role, or even effective in that capacity. And the distinction grows even more stark when rounds of VC move those founders up to managerial roles.

Successful startups are honest about the need for fewer generalists and more specialists as their companies grow. And they become adept, however uncomfortable the process may be, at helping people move on when the time is right. Even when those people helped launch the company from a dorm room.

Hear the rest of Calacanis’s points in his own distinctive voice.

Posted on Mon, March 25, 2019
by NetSuite filed under

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AI will be a blessing, not a threat, to consumer privacy

March 31, 2019 Big Data

Real-world applications of artificial intelligence are skyrocketing. According to the World Intellectual Property Organization (WIPO), patent submissions related to AI nearly tripled between 2013 and 2017 to more than 55,000 applications. This rise in patenting activity reflects the gold rush currently underway in the realm of AI. We can expect to see it becoming essential across almost every industry.

The rapid rise in AI applications has also sparked concern that such technologies pose a threat to consumer privacy by letting companies observe users more closely. But I believe we will actually see quite the opposite effect: Rather than delving deeper into the personal lives of consumers, AI could become actually grant people more privacy.

With great power…

In marketing, I’ve heard some people say that applications of AI have been all talk and little action. But that doesn’t tell the whole story. Every company executive I speak with cites AI as one of his or her company’s top three marketing priorities — even above other hot concepts like blockchain. The desire for AI in marketing is high, and companies are beginning to invest in this realm.

That said, there’s still a great deal of confusion surrounding concepts and terminology when you discuss AI within the marketing field. In fact, I’d say about half of what is referred to as “AI” within industry presentations and panel discussions isn’t AI at all, but rather simple algorithms. This isn’t a trivial distinction. With algorithms, the output is only as good as the data continually fed into it. With AI, the system learns, evolves and extrapolates over time. It can come to conclusions that weren’t initially fed into it.

This distinction is important because, over the next few years, we’re going to see many areas currently controlled by algorithms become AI-driven instead. Think about the personalization of ad content, for example. Algorithmically-generated dynamic ads have been in use for quite some time. But in the future, AI will help to generate these ads on an individual basis and, thus, achieve higher response rates.

… Comes great responsibility

It’s understandable that the concept of true one-to-one marketing raises privacy questions. With the GDPR already in place — and with the upcoming ePrivacy regulation in the EU and the California Consumer Privacy Act in the U.S. — doesn’t personalized advertising powered by artificial intelligence fall by the wayside? Quite the opposite, actually.

In reality, AI doesn’t have to have anything to do with personal data. By using AI (versus simple algorithms) to target advertising more effectively, the importance of personal data will decrease. If an advertiser can reliably identify a consumer type based on online behavior, then the advertiser does not even have to know who that person is in order to deliver the optimal ad. That’s the power of AI and its next-gen learning capabilities. It will be able to determine tendencies and recommendations from users’ online behavior, thereby generating ads that are perfectly created and placed. At present, advertisers require personal data to achieve the same effect. AI can help that take place anonymously.

Of course, this isn’t to say that data collection and regulation are going to become obsolete. When companies interact directly with consumers, they’re still going to want to collect data that enables them to deepen the relationship. But these first-party data relationships are desirable on both sides and well understood by consumers. It’s the behind-the-scenes collection, selling, and trading of data — the activities that most disturb consumers and regulators today — that are going to become far less relevant in an AI-driven marketing world.

As with any emerging technology, AI carries the potential for exploitation. That’s why raising awareness around AI capabilities and real-world applications is so important. As in so many areas, transparency needs to be our industry’s guiding principle when it comes to AI applications in marketing. By emphasizing collaboration and the elevation of good actors within the industry, we can guide new AI capabilities to a place where they alleviate, rather than worsen, consumer concerns around privacy.

Arndt Groth is President at Smaato.

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3 Email Deliverability Best Practices to Help You Improve Inbox Placement

March 31, 2019 CRM News and Info

Deliverability is a hot topic that many marketers are still trying to wrap their heads around. Although the goal of placing emails in the inbox seems simple, there are several factors that influence deliverability — making it difficult for senders to even begin to assess how it applies to their own email marketing efforts.

In simplest terms, deliverability refers to the overall health of a sender’s email. Narrowing down on the true meaning of this term gets complicated, however, when you take into account that the health of your emails involves everything from delivery rate, inbox rate, and ROI from email — among many other factors.

While the term seems unnecessary complex, deliverability is a marketing essential that can’t be ignored. Further, it impacts our ability to do business in an environment where email marketing is more important than ever, especially when it comes to nurturing leads throughout the sales cycle. And with ISPs constantly changing the email landscape in an effort to eliminate spammers, ensuring inbox delivery requires us to follow best practices and stay ahead of the curve when it comes to new updates.

Today, we are going to take some of the mystery out of deliverability and equip you with a few practical tips to set you up for success. The following best practices will help you build a solid foundation for improved deliverability, helping you get your messages in front of your audience.

Design Your Emails to Be Mobile-Friendly

Most consumers and businesses view their email on their mobile devices. ISPs have noted this preference and are now quick to reject your emails or send them to the spam folder they are not mobile-friendly. Therefore, ensuring that your email can be viewed across a variety of devices and email platforms is an important step toward achieving good deliverability.

The right marketing automation platform can help you guarantee your email is easy to read regardless of the device or ISP used by your recipient. Act-On, for example, has a variety of easy-to-use responsive email templates, making it so that you don’t have to know HTML to ensure your message can be viewed across an array of devices. Additionally, our platform uses Litmus to help you see how your email renders on desktop and mobile (and in different email readers), helping you ensure your message is good to go before hitting “Send.”

Ensure Your Emails Are Optimized for the Inbox

Content and design also play an important role in the overall deliverability of your emails. After all, your recipients aren’t the only individuals who view your messages. ISPs, such as Google, scan your emails to make sure they fit certain criteria before they can make it to the inbox. These include design and content elements such as a clear and visible CTAs, alt-text, and copy that resonates with the interest of your recipient.

While these strategies won’t guarantee 100% inbox placement, ensuring your emails conform to the following best practices will help get your message in front of the right audience:

The recipients of this email are targeted for this message
This email is part of a strategy
The subject line is clear and concise and conveys the who, what, where, when, why, and how (whenever applicable)
The email has a clear call to action that results in a click
All links work and lead to secure sites
All pictures have alt-text
The email renders on mobile and the majority of email applications

If your emails meet the criteria above, they’re far less likely to be filtered out or lost in the clutter. These tips also improve the look, feel, and readability of your emails, which ultimately enables you to improve engagement and conversions.

Always Use Quality Data and Maintain Good Email Hygiene

Previously, companies could purchase lists with very few repercussions, but those days are gone forever. Nowadays, it’s more important than ever to ensure you’re collecting quality data and your lists are as clean as possible, which means your recipients are opting in to receive communications from you and that you are collecting valid email addresses.

At Act-On, we take data and email hygiene very seriously. At the end of the day, we want our customers to get results from their marketing, and improving their email deliverability and ensuring they don’t gain a bad email reputation is an important part of doing that. That is why we provide a variety of landing page and form templates that allow customers to easily acquire user information and consent to send all in one place. Our platform also integrates with NeverBounce so that Act-On users can review their lists, make sure all their emails are valid, and reduce the number of hard bouncebacks.

With an array of privacy regulations (such as GDPR) being developed, implemented, and enforced all over the world, it’s in your best interest to ensure you have permission to send and are sending to active email addresses. Further, taking the extra step to gain permission to send emails to your contacts will result in better and more engaged leads, so the work involved in maintaining your lists is really a blessing in disguise.

If you want to learn more about how you can ensure quality data and email hygiene, check out the latest in our deliverability eBook series, Improve Email Deliverability with Quality Data and Email Hygiene.

Stay Ahead of The Game to Ensure Your Messages Reach the Inbox

Deliverability is constantly changing, so it’s in your best interest to stay on top of trends and make sure you are always following best practices. Doing so will set you up for success today and help you avoid having to put out any fires in the future.

This post just begins to cover the basics of what you can do to ensure maximum deliverability rates. We invite you to take a more in-depth view into deliverability and how you can set your company up for success by downloading our Deliverability 101 series, written by Act-On’s very own deliverability consultants, linked below.

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Culture Eats Strategy For Breakfast, Innovation For Lunch, And Transformation For Dinner

March 31, 2019 BI News and Info

Recently I was invited to participate in a panel at #DigitalTakover, the biggest event on digital transformation in southeast Europe. The topic was Everything can be reduced to an algorithm – except employees.

To prepare for the discussion, I asked people about their point of view. Their answers were unanimous: “Of course, employees are the most important asset in every company!”

That got me thinking: How many companies actually really live by the belief that employees are their most important asset?

If the answer is such a no-brainer, why are we even discussing it? If you really think about it, how many people do you actually know who love their job and the company they work for? How many people would honestly say that their company treats them as the most valuable asset?

In today’s time of digital transformation, the truth about whether companies live by the value of putting the employees first is reflected in the organization’s culture.

Back in the last century, Peter Drucker said, “Culture eats strategy for breakfast!” This statement holds true today. I would add that the same culture will eat innovation for lunch, and transformation for dinner. What I mean is that the organizational culture defines the way companies innovate and ultimately how they transform.

Fast-forward a few decades, and we can see that the economies that have evolved from agrarian through industrial to service now have evolved into the “experience economy.” Now more than ever, companies should focus on fostering a culture that defines clear values and providing a quality experience to both to their employees and their customers.

The reality, though, is that companies are really struggling to define their culture and stay true to their values. As Simon Sinek puts it, “Most leaders don’t even know the game they are in.”

You are what you eat: Define your culture

As in dieting, companies become what they eat. If they value teamwork, they will become team-oriented. If they live innovation, they will become innovative. If they foster change, they will become agile. But if they preach a healthy lifestyle and secretly eat junk food, companies cannot stay healthy.

So, if your company aims to survive in today’s fast-changing business environment, you need to answer these questions:

Who are you?
What do you believe in?
What’s your purpose? Why you are doing what you are doing?

Once you know your culture and you have defined clear values and beliefs, you will attract employees who will strengthen your business’s health and help you deliver on the defined strategy.

Take the risk – try new flavors!

Diversity is good: It fuels innovation.

As you develop a healthy culture, let your employees add their own spice – encourage them to share ideas, opinions, different solutions, critical thinking. Give them the freedom to add flavor to your business through innovation and diversity. Give them a chance to express themselves.

All you have to do is to provide an environment where it’s OK to make mistakes, take risks, and even be part of a failure. Fail quickly, learn the lesson, and move on to the next quest. For example, check out the story of Astro Teller from Google X.

Are you eating the right things? If you want to stay fit, make sure you transform the way you eat. As in this video from Raj Ramesh, an organization, just like an individual, needs to focus on the right factors in order to stay fit. In my experience, 70% of diets fail. According to McKinsey, 70% of business transformations fail.

When we speak about digital transformation, we usually look at processes, business models, and technology. Similarly, when we want to lose weight, we focus on physical exercise and watching the scale. But these factors comprise only 20% of the effort; the 80% that really matters involves what, when, and how we eat.

So why do we focus on the irrelevant factors? The answer is simple: Because it is easier. It is very human to take the path of least resistance. Going to the gym and doing sports is much easier than changing poor eating behavior and habits. (Is there anything better than enjoying a bucket of ice cream while you watch a movie before bed?)

However, if you want to lose weight for good, you need to change the timing and the kind of food that you eat. In the same way, organizations that wish to see successful transformations need to focus on their employees.

As a leader, if you want an organizational transformation to succeed, focus on empowering your employees to lead the transformation. Transform the individual to transform the collective. Lead by example and build a vision of the future that employees can relate to – and when things get tough, don’t let up!

In that context, a statement like “My people are my organization’s true asset” will taste very good.

Bon appetit! Stay fit!

What is your organization’s recipe for leading a successful digital transformation?

For more digital transformation strategies, see “3 Tips For Bringing Digital Transformation To An Entire Enterprise.”

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Digitalist Magazine

Power BI open-platform connectivity with XMLA endpoints public preview

March 30, 2019 Self-Service BI

Organizations embracing a data culture must find a way to create semantic models that serve as the single source of truth for the enterprise. With the sophisticated data modeling capabilities in Power BI, customers are building enterprise grade semantic models directly into Power BI datasets, which are then visualized on Power BI reports and dashboards.

We are excited to announce the public preview of read-only XMLA endpoints in Power BI Premium. XMLA endpoints enable open-platform connectivity to Power BI datasets. With these capabilities, customers can leverage a single one-version-of-the-truth semantic model across a range of data-visualization tools from different vendors, including many of those covered by the Gartner Magic Quadrant for Analytics and Business Intelligence Platforms.

Analysis Services in Power BI

Azure Analysis Services and SQL Server Analysis Services are based on mature BI engine technology used by countless enterprises for over two decades. The same technology is also at the foundation of Power BI and is powering its datasets. XMLA endpoints provide access to the Analysis Services engine in the Power BI service. With these endpoints, the same Enterprise BI tools that connect to Analysis Services for application lifecycle management, governance, complex semantic modeling, debugging, and monitoring will be enabled with Power BI.

CentralizedBI Power BI open platform connectivity with XMLA endpoints public preview

Microsoft’s deep heritage in enterprise BI

XMLA endpoints are rooted in Microsoft’s deep heritage in enterprise BI, which uniquely positions Power BI to converge both enterprise and self-service BI in a single platform. XMLA has long been accepted as the industry standard for data access in analytical systems and enjoys wide adoption from many software vendors.

Client tools that work with read-only XMLA endpoints

The following tools can add customer value with read-only XMLA endpoints to Power BI datasets:

Tool	Description	Installation/prerequisites
Third party data-visualization tools	Non-Microsoft tools to consume reusable semantic models in Power BI.	Install the latest versions of MSOLAP from here.
SQL Server Management Studio (SSMS)	SSMS can be used to, for example, view partitions generated by incremental refresh.	The SSMS download is available here. Version 18.0 RC1 or above is required.
SQL Server Profiler	Tool for tracing and debugging.	SSMS 18.0 RC1 or above is required.
DAX Studio	Open-source, community tool for executing and analyzing DAX queries against Analysis Services. We want to recognize the great work already done in DAX Studio to work with XMLA endpoints in Power BI.	Version 2.8.2 or above.
Paginated reports in Power BI Premium, Power BI Report Server and SQL Server Reporting Services	Operational, pixel perfect, paginated reports.	Will be supported in upcoming releases.
Excel PivotTables	Traditional interactive analysis. Note this is already provided by Analyze in Excel (see licensing change below).	The upcoming Click-to-Run version of Office 16.0.11326.10000 or above is required.

The ADOMD.NET client library can be downloaded from here. It provides a programmatic way of executing MDX and DAX queries against Analysis Services for client tools.

Dynamic Management Views (DMV) provide visibility of dataset metadata, lineage and resource usage.

All operations are limited to, at most, Analysis Services database-admin permissions. Some DMVs for example are not currently accessible because they require Analysis Services server-admin permissions. SQL Profiler traces are limited to database-level events.

Addressing a workspace

With the client tools listed above, use the following URL format to address a workspace as though it were an Analysis Services server name.

powerbi://api.powerbi.com/v1.0/myorg/[your workspace name]

myorg can be replaced with your tenant name (e.g. “mycompany.com”).

[your workspace name] is case sensitive and can include spaces.

You can easily copy the workspace URL from the workspace settings dialog.

Copy workspace URL 300x282 Power BI open platform connectivity with XMLA endpoints public preview

When using the URL, depending on the tool (for example SQL Profiler), you may need to specify Initial Catalog. How to specify it is shown in the following example using SSMS.

SSMS connection Power BI open platform connectivity with XMLA endpoints public preview

Power BI apps

Users with permissions to read from datasets through published apps can use the same URL format as addressing a workspace, but the app name replaces the workspace name.

Licensing for XMLA

Access to XMLA endpoints is available for datasets in Power BI Premium. Any user and client can connect through XMLA, regardless of whether the user has a Pro license.

Analyze in Excel allows users to create Excel PivotTables connected to Power BI datasets. Behind the scenes, Analyze in Excel uses a private version of the XMLA endpoint. As part of the broader release of XMLA, we are aligning the licensing of Analyze in Excel on Premium datasets to match the overall approach described above for XMLA. This means that any user will be able to use Analyze in Excel on datasets in Power BI Premium. For datasets not in Premium, Analyze in Excel will continue to function as-is, requiring a Pro license to use.

Security requirements

The tenant-level Analyze in Excel setting in the Power BI Admin Portal must be enabled for the current user.

The new capacity-level setting for XMLA endpoints must be enabled by setting the value to 1 for read only. It is enabled by default.

Capacity admin setting Power BI open platform connectivity with XMLA endpoints public preview

Assuming both the above settings are enabled, access through XMLA endpoints will honor the security group membership set at the workspace/app level.

Workspace contributors and above have write access to the dataset and are therefore equivalent to Analysis Services database admins. They can run database-level traces in SQL Profiler and script out tabular metadata in SSMS.
App viewers are equivalent to Analysis Services database readers. They can connect and browse datasets for data consumption and visualization, but they cannot see internal metadata.

Further information is available on the Docs page.

Read/write coming soon

We are working on allowing read/write operations through the XMLA endpoint. It will come later. With read/write, the following tools will be particularly useful in addition to those listed above:

Tool	Description
SQL Server Data Tools	Model authoring with a range of enterprise features, integration with source control, and application-lifecycle management processes.
SQL Server Management Studio	Perform fine-grain data refresh, scripting and management.
Tabular Editor	Open-source, community tool with extensive set of enterprise modelling features, and easy-to-use experience
Power BI ALM Toolkit and BISM Normalizer	Application-lifecycle management, incremental deployments and model merging as described in this whitepaper
Others	Analysis Services has a rich history of open-source community tools. Various third-party software vendors provide tools for monitoring and managing Analysis Services.

Dataset-level operations and interfaces exposed by the following programming and scripting languages will work.

The Tabular Object Model (TOM) client library is available here. It allows programmatic creation of models and administrative functions like importing and refreshing data.
Tabular Model Scripting Language provides scripting commands that are typically executed from, but not limited to, SSMS.
PowerShell cmdlets for administrative functions and database-management tasks.

Video

This recording from Ignite 2018 discusses the benefits of XMLA endpoints and includes a demonstration of SQL Server Management Studio connecting to a Power BI workspace to manage datasets.
[embedded content]

Final note

Customers value openness and interoperability, and we in the Power BI team continue to make investments to make Power BI the most open BI product in the market.

Over three years ago, we introduced the Power BI custom visualization framework. It has generated hundreds of community visuals and thousands of uniquely customized visuals for specific customers. This demonstrates our commitment to an open, standards-based approach to data visualization.

In November 2018 we shipped Power BI dataflows to bring data in Power BI to an HDFS compatible data lake – Azure Data Lake Storage Gen2 using the Common Data Model (CDM) format. The CDM is an open, standard metadata system for consistency of data and its meaning across applications and business processes. This ensures that data ingested through Power BI dataflows is available to data engineers and data scientists to leverage the full power of Azure Data Services. The CDM continues to evolve as part of the Open Data Initiative.

By now supporting XMLA endpoints we continue our journey of making Power BI more open and extensible, providing access to semantic model in Power BI from any BI tool in the market.

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Love it or Hate It: Auto ML is Here to Stay

March 30, 2019 TIBCO Spotfire

In the data and analytics world, trends come and go. A few years ago, the term “big data” was all the rave.Now, it is simply an implicit capability that many organizations possess. More recently, however, I’ve been in many meetings where terms like artificial intelligence (AI) and Auto ML (automated machine learning) have been making their way into the buzzword bingo cards.

For this blog, we’ll put AI aside for the moment and chat about Auto ML. Conceptually, Auto ML is an umbrella term used to describe a set of processes that are well, automatic and require little to no code. Essentially, these processes may involve automatic:

Data prep and cleansing routines
Creation of new features to be used in machine learning models
Selection of which parameters are to be used in the model
Model identification and selection
Hyperparameter tuning

This automation is packed with promises. Some vendors claim that the intention of this technology is for it to be used by citizen data scientists (or non-experts) to address the skills shortage in the industry and that in some cases data scientists will no longer be needed. Quite simply, for a majority of use cases, it would extremely risky to deploy models without vetting and validation so we would not recommend this approach.

For organizations new to Auto ML, the thought of deploying algorithms into mission critical business systems without proper vetting and testing should throw up a red flag. In order for ML to work, data scientists are a crucial factor. There is still a use for Auto ML in many organizations, but it will not displace or replace our coveted data science unicorns.

Auto ML will augment the work of data scientists, not replace it Recently, I had the good fortune to chat with a group of experts on the topic. To sum up the conversations, we concluded that Auto ML is most useful to augment the work of data scientists and citizen data scientists. Auto ML will be most effective when organizations use it to quickly identify which areas or projects might be most valuable for further exploration by a data scientist. It can also be used as an aid to data scientists to increase their productivity. Auto ML may also help to increase the accuracy of their final solutions, by helping the data scientist quickly consider a wider range of analytic approaches.

But buyer beware, when looking at Auto ML, consider these questions:

Is the Auto ML transparent? That is, can you explain why the model makes a particular recommendation? This is critical for many applications and is imperative for many regulations.
Is the Auto ML extensible and flexible? Can you customize and extend the pipeline generated to suit your specific needs?
What is the workflow and process to vet and deploy the models generated?
After you deploy the machine learning pipelines, how will you monitor, manage, refresh, and govern the deployment?

To find out more about AutoML and how it can benefit your business, watch this YouTube tutorial video.

Next up, artificial intelligence. Stay tuned for my next blog as we discuss the growing importance of “thinking” computer systems.

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The TIBCO Blog

Cat and Dog Work Together To Overcome Obstacle

March 30, 2019 Humor

Sometimes a little help is all that is needed.

“Fighting against segragation of the species.”
Image courtesy of https://imgur.com/gallery/5nNn90j.

Monthly Archives: March 2019

Using the Contact Center to Help Build Brand Loyalty

Customer Service Is Increasingly Data-Driven

Customer Support Platforms in the Cloud

Smartphone-Enabled Customer Support

Getting More Data From More Devices

Context-Awareness Maximizes Customer Service Satisfaction and Agent Productivity

‘Intelligent Automation’ Will Further Enhance Contact Center Effectiveness

Getting Started

Driving Change In Utilities – It’s Not Just A Pipe Dream

more Trump wrestling rhetoric as his insults wear thin

Key Tips for Scaling Your Startup from Jason Calacanis

AI will be a blessing, not a threat, to consumer privacy

With great power…

… Comes great responsibility

3 Email Deliverability Best Practices to Help You Improve Inbox Placement

Design Your Emails to Be Mobile-Friendly

Ensure Your Emails Are Optimized for the Inbox

Always Use Quality Data and Maintain Good Email Hygiene

Stay Ahead of The Game to Ensure Your Messages Reach the Inbox

Culture Eats Strategy For Breakfast, Innovation For Lunch, And Transformation For Dinner

You are what you eat: Define your culture

Take the risk – try new flavors!

Power BI open-platform connectivity with XMLA endpoints public preview

Analysis Services in Power BI

Microsoft’s deep heritage in enterprise BI

Client tools that work with read-only XMLA endpoints

Addressing a workspace

Power BI apps

Licensing for XMLA

Security requirements

Read/write coming soon

Video

Final note

Love it or Hate It: Auto ML is Here to Stay

Cat and Dog Work Together To Overcome Obstacle

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