• Home
  • About Us
  • Contact Us
  • Privacy Policy
  • Special Offers
Business Intelligence Info
  • Business Intelligence
    • BI News and Info
    • Big Data
    • Mobile and Cloud
    • Self-Service BI
  • CRM
    • CRM News and Info
    • InfusionSoft
    • Microsoft Dynamics CRM
    • NetSuite
    • OnContact
    • Salesforce
    • Workbooks
  • Data Mining
    • Pentaho
    • Sisense
    • Tableau
    • TIBCO Spotfire
  • Data Warehousing
    • DWH News and Info
    • IBM DB2
    • Microsoft SQL Server
    • Oracle
    • Teradata
  • Predictive Analytics
    • FICO
    • KNIME
    • Mathematica
    • Matlab
    • Minitab
    • RapidMiner
    • Revolution
    • SAP
    • SAS/SPSS
  • Humor

How Olay used AI to double its conversion rate

July 19, 2018   Big Data
 How Olay used AI to double its conversion rate

Olay, the popular skin care brand, started using AI to make recommendations to its millions of users almost two years ago, and says it has doubled the company’s sales conversion rate overall.

It’s just the latest retail company that has turned to AI to boost its engagement with users to increase its top line. The traction confirms surveys that show an increasing number of businesses are putting AI investments at the head of their agenda.

True, Olay has an advantage over most companies. The billion-dollar brand is owned by giant Procter & Gamble, and has been using AI in its core product for some time. It has 25 years of expertise in image recognition, which helps it identify skin problems and improvement areas for its users.

In 2016, with renewed excitement growing around the potential of AI in marketing products, Olay leveraged the technology in a new marketing push, launching the Olay Skin Advisor, an online tool that gives women an accurate skin-age estimate and recommendations for care.

The product is based on a single selfie, and leverages Olay’s image expertise. Skin Advisor offers up a personalized product regimen, taking into account problem areas it sees, as well as what the user tells it they are most concerned about (wrinkles, crow’s feet, dry skin, etc.).

It incorporates an AI-powered matching engine built by Nara Logics, a Boston company that specializes in content matching and also serves the CIA, among others. Its technology decides exactly which of Olay’s 100 or so products to recommend, and in what combinations.

We talked with the CEO of Nara Logics, Jana Eggers (see video below), about how Olay doubled its conversion rate with the Skin Advisor product, which now has engaged more than four million customers. Skin Advisor also increased the average basket size, for example increasing it by 40 percent in China alone, and cut the bounce rate of visitors to a third of what it was previously. While P&G doesn’t break out Olay results in its earnings, it recently cited demand for Olay products as a reason for exceeding expected sales.

It’s one of the series of cases we’ve been writing about in the run-up to our Transform event on August 21-22, where we are showcasing real examples of companies using AI to drive their business results. Our motto for the event has become “You can do it too!,” because it’s not just the big tech companies — Google, Amazon, Facebook — that can use AI.

Here are my six take-aways from the interview:

  • AI approaches are customized per industry. Nara Logics uses the same machine learning algorithm for Olay as it does for the U.S. government’s intelligence community. But it generates unique “knowledge graphs” for each industry. For Olay, the algorithm accommodates two requirements: First, rules track individual product features and ingredients, to ensure they’re matched to customers’ focus areas and complement each other when offered in suites. Second, it gauges what products are popular, from reviews, transactions and other sources: Moisturizers may be healthy, but women like light hydration moisturizers, not sticky ones. This incorporates a collaborative filtering approach similar to the recommendations from Amazon or Netflix.
  • You don’t have to hire Ph.D.s. Eggers says that while the giant AI-platform companies like Google, Amazon, and Microsoft are hiring data science Ph.D.s, most companies don’t have to hire these expensive employees. “Hire some great software engineers,” she says, and they’ll be excited about using these technologies.
  • Neural nets may be hyped, but they’re still useful. Eggers agrees that neural nets, a deep learning approach, had become overhyped last year. She says she’s seeing more balance now; some companies are moving away from that hype. That said, Nara Logics does use neural nets for collaborative filtering analysis or natural language processing. It also uses proprietary algorithms to filter out noise.
  • Retail, financial, and B2B sectors are ripe for AI. Eggers sees the retail and financial industries are moving quickly to adopt AI. She’s also seeing a lot of traction at B2B companies. These companies have discovered they’re not selling their services to other companies so much as they are selling them to individuals within those companies. This requires AI that makes recommendations based on what those people need in their specific roles.
  • It’s all about personalization. Skin Advisor serves recommendations to tens of thousands of people very week, and yet 94 percent of users receive recommendations unique to them — meaning no one else has received the same recommendation.
  • Men: Use it inside, or shave or something. Not sure if it was a bug or not, but when I first tried Skin Advisor, I was sitting outside, and it thought I was 59. I’m only 51. A couple of hours later, I tried it indoors, and it guessed 51. Bingo. (Later, I was told Skin Advisor doesn’t like men’s facial hair, so maybe that was it.)

This is just part of the story. Join us at Transform (ticket link here) where Jana Eggers sits down with Procter & Gamble’s Christi Putman, R&D Associate Director & Damon Frost, CIO-Beauty to hear more about how Olay is harnessing the power of AI.”

Thanks to all of our sponsors whose support makes Transform possible: Samsung, Worldpay, IBM, Helpshift, PullString, Yva, TiE Inflect and Alegion.

Let’s block ads! (Why?)

Big Data – VentureBeat

conversion, double, Olay, Rate, used
  • Recent Posts

    • TripleBlind raises $8.2 million for its encrypted data science platform
    • Ba’al comes to CPAC, Ted Cruz jokes about his Cancun trip
    • Optimizing data migration/integration with Power Platform
    • AI Weekly: Biden calls for $37 billion to address chip shortage
    • NOT WHAT THEY MEANT BY “BUILDING ON THE BACKS OF….”
  • Categories

  • Archives

    • March 2021
    • February 2021
    • January 2021
    • December 2020
    • November 2020
    • October 2020
    • September 2020
    • August 2020
    • July 2020
    • June 2020
    • May 2020
    • April 2020
    • March 2020
    • February 2020
    • January 2020
    • December 2019
    • November 2019
    • October 2019
    • September 2019
    • August 2019
    • July 2019
    • June 2019
    • May 2019
    • April 2019
    • March 2019
    • February 2019
    • January 2019
    • December 2018
    • November 2018
    • October 2018
    • September 2018
    • August 2018
    • July 2018
    • June 2018
    • May 2018
    • April 2018
    • March 2018
    • February 2018
    • January 2018
    • December 2017
    • November 2017
    • October 2017
    • September 2017
    • August 2017
    • July 2017
    • June 2017
    • May 2017
    • April 2017
    • March 2017
    • February 2017
    • January 2017
    • December 2016
    • November 2016
    • October 2016
    • September 2016
    • August 2016
    • July 2016
    • June 2016
    • May 2016
    • April 2016
    • March 2016
    • February 2016
    • January 2016
    • December 2015
    • November 2015
    • October 2015
    • September 2015
    • August 2015
    • July 2015
    • June 2015
    • May 2015
    • April 2015
    • March 2015
    • February 2015
    • January 2015
    • December 2014
    • November 2014
© 2021 Business Intelligence Info
Power BI Training | G Com Solutions Limited