Marketing data analytics
Upcoming SlideShare
Loading in...5
×
 

Like this? Share it with your network

Share

Marketing data analytics

on

  • 4,703 views

Leverage all the customer data you have collected over the years and use these simple data analytic techniques to align your marketing expense better and identify your best customers.

Leverage all the customer data you have collected over the years and use these simple data analytic techniques to align your marketing expense better and identify your best customers.

Statistics

Views

Total Views
4,703
Views on SlideShare
2,977
Embed Views
1,726

Actions

Likes
2
Downloads
93
Comments
0

16 Embeds 1,726

http://www.scoop.it 1314
http://blog.canvass.in 326
http://university.canvass.in 51
http://uni.zirconweb.com 11
https://twitter.com 5
http://www.google.com 3
http://www.linkedin.com 3
http://boutofcontext.com 3
http://search.yahoo.com 2
http://translate.googleusercontent.com 2
http://webcache.googleusercontent.com 1
http://feeds.feedburner.com 1
http://yandex.ru 1
https://hootsuite.scoop.it 1
http://www.redditmedia.com 1
http://inbound.org 1
More...

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Marketing data analytics Presentation Transcript

  • 1. Copyright: Canvass 2013-2016 Marketing Data Analytics – The future of Marketing Success
  • 2. Copyright: Canvass 2013-2016 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!
  • 3. Copyright: Canvass 2013-2016 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
  • 4. Copyright: Canvass 2013-2016 Simple steps to get you started with Data Analytics
  • 5. Copyright: Canvass 2013-2016 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.
  • 6. Copyright: Canvass 2013-2016 Collect Data about your Customer Where to collect? • Website • Social media • Landing pages • In-store tablets • Marketing tools capturing user behavior
  • 7. Copyright: Canvass 2013-2016 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
  • 8. Copyright: Canvass 2013-2016 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)
  • 9. Copyright: Canvass 2013-2016 Your data is ready. Let’s generate insight into your customers
  • 10. Copyright: Canvass 2013-2016 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
  • 11. Copyright: Canvass 2013-2016 RFM (Recency, Frequency, Monetary)
  • 12. Copyright: Canvass 2013-2016 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
  • 13. Copyright: Canvass 2013-2016 How can RFM benefit you?  80% of your business comes from 20% of your customers  your most important customers more accurately
  • 14. Copyright: Canvass 2013-2016 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.
  • 15. Copyright: Canvass 2013-2016 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.
  • 16. Copyright: Canvass 2013-2016 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
  • 17. Copyright: Canvass 2013-2016 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
  • 18. Copyright: Canvass 2013-2016 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
  • 19. Copyright: Canvass 2013-2016 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
  • 20. Copyright: Canvass 2013-2016 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
  • 21. Copyright: Canvass 2013-2016 LTVC (Life Time Value of a Customer)
  • 22. Copyright: Canvass 2013-2016 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.
  • 23. Copyright: Canvass 2013-2016 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
  • 24. Copyright: Canvass 2013-2016 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/
  • 25. Copyright: Canvass 2013-2016 Calculating LTVC – Step 2 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%
  • 26. Copyright: Canvass 2013-2016 Calculating LTVC – Step 3  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
  • 27. Copyright: Canvass 2013-2016 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
  • 28. Copyright: Canvass 2013-2016 Segmentation & Clustering
  • 29. Copyright: Canvass 2013-2016 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
  • 30. Copyright: Canvass 2013-2016 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
  • 31. Copyright: Canvass 2013-2016 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
  • 32. Copyright: Canvass 2013-2016 Example - Clusters using Age, Income & Recency
  • 33. Copyright: Canvass 2013-2016 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
  • 34. Copyright: Canvass 2013-2016 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!
  • 35. Copyright: Canvass 2013-2016 Ankur Nandu COO, Canvass Inc. ankur@canvass.in LinkedIn Canvass All-in-one Marketing Software
  • 36. Copyright: Canvass 2013-2016 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