Analytics for Effective Marketing Strategy

Over the past decade role of the Marketer with any major retailer has become quite interesting and complex as they blend

multiple customer touch points (brick & mortar, online, mobile and social media) to achieve their goals.

The marketer understands their customer’s pulse and with the limited budget in hand, strategically work to attract, retain

and grow their customer base. At times their strategies are successful and they are able to generate high Marketing ROI

(Return on Investment). They attribute their success (no doubt) to rigorous planning (ATL/BTL activities) that incorporates

development of creative campaigns and attractive promotions to get customers buy their products.

At another time the campaigns/promotions may not work and lead to low or negative Marketing ROI. Marketers then try

to understand the reasons and the most common ones are incorrect marketing to target customers, channel selection,

change in consumer dynamics (preferences, buying patterns), competitive landscape and economy. Many times, the base

of these reasons are backed by gut feelings, business experience, ground level insights and some data insights. But are

these factors included when planning a campaign?

Are there any other

factors that were

not included?

Which factor (or

data point)

primarily impact

the campaign/

POS

Store

Product

Price

Calendar

Customer

Demographics

Purchase behavior

Marketing

Media Spend

Media-Channel

Promotion

Social Media

Sentiment

Themes

Influencers

External/ Web

Call center

Competition

Survey ratings

Weather

Holidays

Data Sources/Points

promotion? For instance, in one of my project related to marketing campaign effectiveness program, I have to research

and integrate external publically available data related to weather events, temperature, surveys, holidays and competition

with (internal data) promotions, season, store location, format and assortment. This not only helped to identify the key

variables that impact sales but also their magnitude on sales eg. X% change in media spend would increase sales by Y%.

Can we say that the role of marketer is not just to work hard towards (operationally) planning campaigns but also link

their marketing creativity with data science, in order to (at least) prevent negative ROI as a short-term goal and building a

brand as a long term goal?

Additionally, the marketer may not always have the luxury of time and

skills to leverage creativity and data science (at full scale). The marketer

should either possess the requisite data science skill sets or have a

partner (in-crime) to achieve his/her objective.

A partner (a data scientist/

analyst or whatever the name you may call) should understand marketer’s

business objective and address pain-points by providing solutions that are data

science driven. The solution recommendations should feed into Marketing

Operation plan, which in-turn should improve marketing strategy decisions.

Marketing Strategy (1):

Marketers plan their activities in order to acquire, retain and grow their

customer base.

Acquiring new customer: generally is short-term goal achieved through

heavy discounts, BOGO offers etc.

Retaining existing customer: long-term goal achieved through Loyalty

programs and Customer experience.

Growing (thy) customer: long-term goal to engage the customer through personalized strategies.

Marketing Strategy + Data Science Solution (2 & 3):

Business

Strategy

Business Questions Addressed

(Few Use Cases)

Analytics Solution/

Recommendation

Data points Data Science

Techniques

Acquire Which media channel will generate

maximum sales and (or) reach?

What is the demographic profile of

potential customers and what is the

probability of getting response from a

segment having female customers living in

X location with Y income and Z household-

size?

Optimize media spend

by identifying right

channel mix

Location analysis

POS

Customer

Marketing

External/ Web

Social media

Correlation

Regression

Tree models

Bayesian

Retain When should the promotion be launched?

Which SKUs & stores to have special

promotions? Which key factors impact the

promotional sales? What is the ROI

generated from a campaign?

Which customers are likely to be churned?

What is the probability of their churn rate

and the potential revenue at risk?

What are the customer taking about my

brand? What are they (un)satisfied about?

End-to-end campaign

analysis (Planning-

Monitoring-

Effectiveness)

Customer Churn

prediction

Customer Sentiment

analysis (influencers,

key themes,

sentiments)

POS

Customer

Marketing

External/ Web

Social media

Clustering/Tree

models

Logistic/

Classification

Text mining

Sentiment

Grow How to generate high transaction value

from my retained customers?

Is channel X good for customer A than

customer B?

Improve Market share

Personalized offers

POS

Customer

Marketing

Social media

Association rules

(cross-sell/up-sell)

Next Best Offer

About me : I work with Hewlett Packard Enterprise as a Data Scientist and have 13 years’ experience in Predictive

Analytics, Machine Learning, Consulting, Business Intelligence and functional experience in Retail/GPG companies.