Marketing data analytics

Copyright: Canvass 2013-2016
Marketing Data Analytics –
The future of Marketing Success

Successful Marketing is
• sending right content
• over right channel
• at right time
• with right frequency
• to right customers
Analytics can help you determine what is RIGHT!

From identifying your best customers to deciding
where to invest your marketing budget, data
analytics gives you better actionable insight than
ever before.
Source: www.novotech.com

Simple steps to get you started
with Data Analytics

Collect Data about your Customer
What to collect?
• Contact information (name, email, mobile)
• Demographic indicators such as age, gender,
address, marital status.
• Behavioral indicators such as purchase preferences,
preferred medium of communication & brand
engagement, etc.

Collect Data about your Customer
Where to collect?
• Website
• Social media
• Landing pages
• In-store tablets
• Marketing tools capturing user behavior

Clean up the Data
• Remove duplicate data
• Ensure consistency in formatting of the data
• Age is defined in same units – years/months
• Gender is Male/Female across the file
• Update missing data
• Contact customer and get missing information
• Find similar profiles in your database and estimate
• Analyze outlier data separately

Precautions while cleaning up data
• Do not use average/median values to fill empty
spaces
• Personal Biases to fill missing data can result in
significant errors
• Do not run math operations on abstract data
- Abstract data such as City names (Mumbai, Hyderabad,
Bangalore) are assigned numbers 1,2,3 and then averaging may
reveal 2 as the most common city. (Huge mistake in analysis)

Your data is ready.
Let’s generate insight into your customers

Easy & Effective Analytical techniques
• RFM (Recency, Frequency, Monetary)
Will help you identify your best customers
• LTVC (Life Time Value of a Customer)
Will help you evaluate customer cost of acquisition
• Segmentation & Clustering
Will help you run targeted marketing campaigns

RFM
(Recency, Frequency, Monetary)

What is RFM?
RFM analysis is a marketing technique used to
determine your best customers quantitatively by
using information about:
• Recency - How recent was the purchase
• Frequency - How often does the customer purchase
• Monetary - How much has the customer spent
Source: http://searchdatamanagement.techtarget.com/definition/RFM-analysis

How can RFM benefit you?
 80% of your business comes from 20% of your
customers
 your most important customers
more accurately

How can you run RFM?
Using RFM analysis
 Step 1: Assign your customers a ranking number of
1,2,3,4, or 5 (with 5 being highest) for each RFM
parameter.
 Step 2: The three scores together are referred to as an
RFM "cell" .
 Step 3: The database is sorted to determine which
customers were "the best customers" in the past, with a
cell ranking of "555" being ideal.

How can you run RFM?
Example:
Let’s say you own a clothing store and have been in business
for a year.
Some of your customers have bought from the store on 10
occasions in the year while some have bought only once.
Total amount spent by each customer ranges from $100 to
$5000.
Let’s assume you had sales every day in this last year.

RFM Step 1 - Rank Customers
We need to rank individuals for the individual metrics
of Recency, Frequency & Monetary. For the example
considered, the following ranking mechanism could work:
Recency
Ranking
Recency (Days since
last purchase)
5 70 days
4 71 - 140 days
3 141 - 210 days
2 211- 280 days
1 281 - 365 days
Frequency
Ranking
Frequency (number
of purchases)
5 more than 8 times
4 5-7 times
3 3-4 times
2 2 times
1 once
Monetary
Ranking
Monetary
(amount spent)
5 more than $ 4000
4 $ 3000 - $3999
3 $ 2000 - $2999
2 $1000 - $1999
1 less than $1000

RFM Step 2 – Generate RFM Score
Using the scoring system used in the previous slide, we
can generate the RFM Cell Score for all the customers.
Customer Information
RFM Cell Score
Recency
(Days since last
purchase)
Frequency Monetary
555 45 days 10 times $4500
451 123 days 9 times $950
324 156 days 2 times $3600
232 250 days 4 times $1650
111 350 days once $500

RFM Step 3 – Identify Top Customers
We need to sort the RFM Cell Score for all the
customers
Customers with RFM score as 555 are your best
customers while those with 111 are the least desirable
customers

How can you use the RFM Results?
 Reach out to your best customers and make
them feel special
 Make them your brand ambassadors
 Align your marketing expenses better

Common mistakes in using RFM Results
 Do not over-solicit high ranking customers.
 Low ranking customers should not be neglected.
Concerted efforts should be made to nurture
these customers and make them loyal

LTVC
(Life Time Value of a Customer)

What is LTVC?
LTVC (Lifetime value of your customer) is a
great way to identify how much value your
customer will bring to you over his/her lifetime.

How can LTVC benefit you?
 Determining the right amount of money to
invest in acquiring a customer
 Analyze customer acquisition strategy and
solidify your marketing budget

Calculating LTVC – Step 1
Lets take an example
 You are a coffee shop owner and have 100
customers visit you every week. Most customers are
regulars and visit you 5 times a week. On every visit,
they spend about $3.
Source: http://josephratliff.com/blog/calculating-lifetime-value-of-the-customer/

Let’s make the following assumptions:
 On an average, these individuals will remain
coffee consumers for 12 years.
 80% of the customers will repurchase from you in
the following year.
 You make 20% profit margin on every customer
visit
 Rate of Inflation is about 10%

 As can be seen from Appendix 1, simple
calculations can help you determine the Lifetime
value of your customers
 LTVC has been calculated as $4992 per
customer in this example

Using LTVC Results & Refining it
 As long as the LTVC > Customer cost of acquisition, your
marketing expense in acquiring the customer was well
spent
 All your customers are not the same! Repeat the exercise
for different groups/segments of your customers to get
even better results from LTVC

Segmentation & Clustering

What is Segmentation & Clustering?
Customer Segmentation is the subdivision of a
market into discrete customer groups that share
similar characteristics
Clustering is putting together these similar
individuals to target them better and scalably

How can Segmentation benefit you?
 Segmenting allows you to predict behavior of
new customers by simply categorizing them into
a particular cluster
 This helps you run targeted marketing and
service activities helping you increase your ROI
significantly

How can you cluster and segment?
 Pick different criteria like age, gender, education,
spending patterns, communication preferences, etc. to
segment the customers
 Your clustering results depend directly on your creativity
in picking the right parameters and the amount of data
you collect about your customer
 Tools like ME-XL, SPSS, JMP, SAS are relatively low cost
and work very well in converting the data into tangible
results

Example - Clusters using Age, Income & Recency

Have you done a good job?
Identifiability
 Are you able to easily differentiate between segments
Substantiality
 Are your clusters big enough
Accessibility
 Are you able to reach your customers
Stability
 Will these clusters remain stable with time
Actionable
 Are the segments helping with marketing direction
Source: http://www.bisolutions.us/Cluster-Analysis-vs.-Market-Segmentation.php

Simple yet smart marketing data analyticsSimple yet smart marketing data analytics
will really help optimize your marketingwill really help optimize your marketing
spend and ensure you are focusing on thespend and ensure you are focusing on the
right set of customers for your business!right set of customers for your business!

Ankur Nandu
COO, Canvass Inc.
ankur@canvass.in
LinkedIn
Canvass All-in-one Marketing
Software

Appendix 1: Calculating LTVC
Average revenue per customer over the 12 years
52 weeks * 5 visits/wk * $ 3/ visit * 12 years= $9360
Average profit per customer over the 12 years
20% profit margin * Avg. Revenue per customer/yr = $1872
LTVC
Avg. profit/customer * (80% retention rate) / (1+10%inflation-
80%retention rate)
= 1872*0.8/(1+0.1-0.8)
= $4992

Marketing data analytics

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