Define Marketing Success with ML/AI

Predictive analytics is the use of data, statistical algorithms and AI techniques to identify possible future outcomes. This can help you stay ahead of the curve and assess the future of your marketing. Here are a few ways that you can use AI and predictive analytics in your marketing.

Optimizing marketing campaigns

With predictive analytics, it works just like the Scientific Method by having a hypothesis and then proving it either right or wrong. You can use the data to determine what customer segments and audiences will be the most effective to reach and create actionable insights.

With accurate reporting, you can accurately tell whether a campaign was successful and optimize where it may fall short. This lays the groundwork for best practices of strategies to follow, not just in marketing, but sales and business decisions as well.

Predicting customer behavior

Data is the most accurate way to predict a customer’s “next move” in your business model- especially online. Using behavioral data with customer journeys, you can predict engagement points on when you think a customer may convert. You can also track “drop-off points” and see where you may be losing people whether it is due to confusing content or a dead end in the journey.

By mapping these patterns, at both one-to-many and one-to-one marketing, you can give insight into the outcomes of campaigns and help drive to the outcomes that you want.You can also use this information to do profile scoring and build customer models.

According to a study by the Aberdeen Group, predictive analytics users are twice as likely to identify high-value customers and market the right offer. By doing all of this you can identify potential leads and prioritize the ones that are most likely to convert.

Personalizing content

By being able to predict customer behavior and build models off that data, you can then personalize your content to target those certain leads. By targeting the right audience at the right time, you can show more accurate paths to ROI.

By using historical data to see the behavior of past customers, you can use that to determine and create personalized messages.

Easily scale Tailored and Personalized Journeys.


Advanced segmentation dives deep into the behavioural and lifestyle analysis that allows to look at not just demographics, but the actual products like-minded customers are purchasing.  Use sophisticated algorithms to scan high volumes of customer data to groups customers into lifestyle segments.

Identify key customer segments in terms of behaviour, interests, preferences and opportunity through advanced segmentation and visualize customers across key milestones bench marked. With the ability to get as granular as you need across unlimited customer attributes, your ability to segment and deliver targeted communications across relevant touch points is infinite.

Advanced, & Granular Segmentation

By employing advanced segmentation, marketers can group customers on products and behaviors, see how they move between segments, and identify motivations that build messaging that drives behaviour.

Know Your Customer

Deep Segmentation across Customer Segments, Brand Value and Customer Lifestyle can power an Automated Offer Engine. These Customer Indicators Influence and deliver a Next Best Action that engages customers through tailored Product Recommendations, Up sell opportunities, Promotions and Relevant Offers.

Understanding User listening Behavior is essential for Personalizing Music listening experiences on Spotify

Spotify Music Recommenders

Spotify uses machine learning recommenders that take into account what and how users consume playlists and the rich diversity of playlist experiences

User engagement (UE) is a quality of user experience characterized by the depth of an actor’s cognitive, temporal, affective and behavioural investment when interacting with a digital system (O’Brien, 2016a)

User Engagement Metrics

“Our customers always tell us that music discovery and listening is a personal experience, and we are enhancing the free experience with this in mind,” said Babar Zafar, VP of Product Development at Spotify. “This is the beginning of an evolution for Spotify and we will continue to make improvements that mirror our customers’ needs. This is not only about giving users a more customized free experience from the day they sign up, but giving them more control over their listening experience so they can easily find and stream their favorites anytime, from anywhere.”

Insights Engine: Go beyond Transactions data: Gauge the Customer Intent

With Advanced Analytics platform, you can increase your return on investment across marketing, sales, product and category management, by:

Growth for Knowledge (GFK) Consumer Insights Engine
  • Understanding Customers/Prospects
  • Stimulating Demand with Messaging
  • Optimizing Visibility with Marketing Channel Mix
  • Becoming the chosen brand in the target Market
  • Providing the optimal customer product experience
  • Win at every stage of the purchase journey

Empowering Marketing, Sales, Product, and Category Management Business functions to answer key questions with Actionable Insights

  • What triggers the realization of a need to purchase?
  • What channels do consumers use when researching products?
  • What are the important attributes for consumers when deciding to purchase?
  • What do the purchasers think, & talk about the products?
  • How understanding your customer’s purchasing behaviors and decision-making can drive sales.

The Consumer Journey Module is the first, and only solution for Manufacturers, and Retailers in the technology and Consumer Durables Industries to combine the most comprehensive collection of point of sales data with

  • AI Enabled Consumer Review Data
  • Online Consumer Behaviour Data


Right to Play: How Mattel Is Leveraging Its Technology Organization to Drive Cultural Change

Adobe Summit 2019 NOTES

Mattel, due to data regulations; basically, start with persona; and assume that they have no data about their audiences – Data Deficit. Understanding the Customers; a Generation in AI/ML; and 3rd Gen for Data Driven Marketing; how to integrate Human Insights. Thick, & Thin Data… How to contextualize the data to for better Cx; More Behavioral Data; Mannerisms => What to put in Experience, for the Exp to Work.

AI would help in the Heavy Lifting. Sometimes the data is made vanilla; Similar Age Band, Interests, watch you tube, e.g. AG, & Barbie… why they are coming to the brand. Need this understanding to provide specific experiences … parents are more interest for classic experience… need more human insights.

Shift to Experience (from Marketing (what I tell you about the products)). Happy Employees drive Happier Customers. Technology is the equalizer for the Business processes.

Design thinking Mindset. Strategic Business Partner. Experience (in store, digital, product) … no. of domains, expertise, …. CEO Transformation Strategic Partner. Gartner. Operations, Environment in Order. Keep the systems up, secure, run in time. Empathy for the business. What values are adding to the business. Drive efficiency, profitability, impact the revenue.
Measure CIO Vs CMO. Connection between Design, & Tech. Applied Innovation. Deliver experiences when they were Designed. Art of the Possible. Art of the Now. What is the Experience that is being created; can come from anywhere (design, development, …) Cross Functional Team.
UI, UX =, the core is the consumer. Erodes the issue that were Experience sits. Innovation at the edge or in the middle (core). Tech for tech’s stake. Connected Toys Stake. Mixed Play. Price Point. Margins as per Retailers Desire. Tech to be part of the Natural Experience. Stop Work to Automate. Novelty. Play > Tablet > Play (Bad Ex). Tech must be Seamless. Consumer at the core.

Mattel is going through Transformation. Lock Arms. Make them feel Engaged. Natural to Attack Innovation. How to keep Toys Relevant. Political Ecosystem. Every Company is Different, But they all Kind of Same. Talent Acquisition. Training.

Palantir in India to analyze Future Group data

src: Economic times

Future Group has tied up with American data mining firm Palantir Technologies, which will provide the country’s biggest listed retailer with analyses of data on shoppers’ consumption and buying frequency patterns.

Retail Analytics Platform | Src: Market6

“They will analyse customers’ data at an extremely micro level and such detailing will provide insights in customer trends and shopping habits,” said Kishore Biyani, CEO, Future Group. “The technology tie-up is part of our data-to-business strategy called Tathastu, with an aim to get two crore members from stores across formats to spend Rs 1 lakh each per annum.”

A 10-member team from Palantir Technologies is already stationed in India to help Future Group in data science and machine learning algorithms. Most consumer companies and retailers are relying on external data to gauge their sales and plan new launches.

Biyani owns more than half- a-dozen supermarket store chains including Big Bazaar, Hyper City, Easyday and Nilgiri’s that have a combined retail space of 14.8 million sq ft in 340 cities, a national presence that can only be matched by Reliance Retail. With a footfall of about 500 million and transaction data on more than 30 million customers, the company’s shopping data can be used to predict purchases, said Biyani.

Future Group’s dependence on technology to boost sales comes against the backdrop of increasing competition from rivals such as Walmart and Amazon that rely heavily on data mining to push sales growth.

For the past one year, the company has been pushing technology integration, known internally as Retail 3.0, which is being piloted through several Easyday stores that function as a marketplace which are also used to study shopping behaviour. For instance, each member spends nearly Rs 40,000 at small format stores and their purchase frequency is 38-52 times a year. Such collated datapoints are used to predict consumption patterns and even manufacture products.

Google Marketing Platform Explained

Learn about Google Marketing Platform, a unified solution for cross-channel marketing. It includes an integrated set of advertising and analytics products that let you manage the entire customer journey.

Benefits of Google Analytics 360

Learn more about Google Marketing Platform Integrations

Understand the Importance of the Campaign Manager Integration with Google Analytics 360

Learn More about Display & Video 360 reporting integration with Google Analytics 360

What’s the difference between Google Analytics 360, & Campaign Manager, Attribution Models

How to Guide: Display Video 360/Google Analytics 360 Remarketing and Setup

Essentials: Understanding Display Video 360 Reports, Dimensions, and Metrics

Essentials: Understanding Search Ads 360 Reports, Dimensions, and Metrics

Getting started with BigQuery/GA360 integration

Reporting with BigQuery

Custom Funnels in Google Analytics 360

Unsampled Reports, & Custom Tables 1

Unsampled Reports, & Custom Tables 2

Roll up Reporting