Betty Cracker

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  • Betty CrockerCustomer Lifecycle and Behavioral Insights

    Yumeng DuYudi GaoYang LiuDi LiuQiulin Peng

  • 01 02


    Project overview

    Customer Profiling Insights and Recommendation

    Analytics Method


  • Project Objectives

    Profile engaged customers base on Email and website behaviors.

    Identify key engagement factors that would influence propensity to buy across all categories.

    Recommend digital marketing strategies based on the insights derived from data.

  • Website and email behaviors Remove extreme values (age, website visit, open rate, click through rate) Reduce data skewness by taking log of all behavioral variables Factor analysis result:

    Website Opinion: Rate, Review Email Response: Open rate, Click through rate Social Influence: Social share, favorite Content Usage: Print, Website Visit, Email share

    Product categories Factor analysis result:

    Health Conscious: Diet, Fiber, Gluten free, Healthy, Organic, Ready-to-serve soup, Yogurt

    Kids Meal: Kids, Less sugar, Mexican, Protein Baking: Dry baking dough Breakfast & Snack: Bars, Cereal, Strudel

    Analytics Methodology - Factor analysis

  • Age Group Young: 18~33 Early Adulthood: 34~45 Middle age: 46~65 Senior: over 65 years old

    Regression & Interaction Look at the interactions between customer behavior and age group for each product

    category and brand

    Clustering Analysis Old Active Customers and Social Influencers are the most engaged customers

    Analytics Methodology - Age group, Interaction, Clustering

  • Customer Profiling -- Age group, Interaction

    Young Inactive customer

    Old Active Customer Solution Seeker Social Influencer Majority Customer

    Membership >2 months >5 months >4 months >4 months 3 months

    Open Rate 24% 82% 71% 72% 96%

    CTR 9% 33.27% 32.88% 26% 32.90%

    Visit 1.5 5.6 4.2 3.8 2.5

    Print Rate 4% 34% 60% 6% 3%

    Social Share 0.4% 6.1% 0.6% 30% 0.7%

    Favorite 1.4% 18.7% 2.7% 40% 1%

  • General Insight

    Engagement behaviors dont have strong influence on overall propensity to buy

    Customer segment

    Engagement rank

    Rank of Propensity to


    Old Active Customer 1 4

    Social Influencer 2 1

    Solution seeker 3 2

    Majority customer 4 3

    Young Inactive Customer 5 5

    But when we break down to category level, the influence increase greatly

  • Product Category Findings

    Health conscious Initial propensity to buy for this category is highest for all age groups, and they are very

    responsive to email activity. Kids meal

    Email has the strongest influence on propensity to buy. Influence gets stronger for older age groups.

    Breakfast & snack Social influence is the strongest factor for propensity to buy, especially for customer in early


    Baking Content usage has the heaviest influence on propensity, so for Progresso. Encourage cooking behavior to upsell and cross sell category

  • General Observations

    Email response and content usage behaviors have the heaviest influence among all age stages.

    Video consumption is insignificant in terms of predicting customers propensity to buy.

    Different age groups have different levels of email responsiveness.

    Customers receive emails with redundant contents within a short period of time.

  • Insight: Content Usage leads to cooking!

    Email Share Print CouponGrocery list

    Recipe Cook

    Share with friend


  • Recommendation: Customer Journey OptimizationEncourage cooking behavior by make cooking easier to spur all category sales!

    Website: Accompany quick videos with recipes, makes cooking look faster and easier Make the recipes cater to smaller serving sizes (1- 2) 2 Printing Options

    Mobile App Create a personal cooking file when customers favorite recipes and

    automatically collect coupons

    Send weekly favorite report on friday, reminding they to shop what they marked as favorite, showing products grouped by categories

    Push notification: use geofencing to identify customers when they enter the store, remind what they marked as favorite - triggers consumption

    Email: Send different category promoting emails content cater to different age groups. Weekly favorite email report, avoiding redundant contents

  • Customer Journey Optimization

    Email respondContent Usage

    Mobile App Website Email

  • kid's meal category Insight Early adulthood customers (34-45) are

    most likely to buy. Mexican food and Kids food customers

    are highly overlapped. Parents feed their kids mexican food.

    Email: Include family context to recipes that promote kids and Mexican food categories.

    Exp. create the best play day experience for your kids with our delicious tater tot Casserole

    Recommendation -- categories

  • Recommendation -- Categories

    Baking Category: cross sale with Progresso) Add This makes a great meal!

    Recommend dessert when customers do print and emailshare on the site. For example, recommend pillsburys baking dessert recipes when customers print progresso soup recipes

    Send emails to encourage and inspire people to cook with two course meal idea.

    Health conscious: Give more weights to health conscious category product in

    emails promotion.

    Breakfast & Snack Website & social media promotion

  • Thank you!

  • Appendix

    Factor analysis for behaviors