Betty CrockerCustomer Lifecycle and Behavioral Insights

Yumeng DuYudi GaoYang LiuDi LiuQiulin Peng

01 02

0403

Project overview

Customer Profiling Insights and Recommendation

Analytics Method

Agenda

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 don’t have strong influence on overall propensity to buy

Customer segment

Engagement rank

Rank of Propensity to

buy

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

adulthood

● 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 customer’s 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

Record

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 pillsbury’s 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