Find out how predictive analytics can advise when sales reps should contact a customer for a sale. Predictive analytics can predict when a customer is ready to buy. As presented at AA-ISP May 2011 Leadership Summit.

1. Calling Customers: It’s About Timeto Stop Guessing Parth R. Srinivasa President, Valgen

2. Session Overview

3. McKinsey & Co. study finds that: 72% “destructive” 35%… calling too often 8% call too little/ignore; 29% lack knowledge Customers can tell calling for calling’s sake! Timing, Relevance , Sequence critical to each touch

4. Why Get Timing Right?

5. Where do you fit in your existing customer’s buying cycle? Call Share/ Learn Aware Discuss

6. Timing pattern… think traffic pattern Traffic lights have their own “algorithm”… number of vehicles, elapsed time, rate of vehicles etc. Wait until customer is ready (nurture) Prioritize, merge (engage) Move, align message + channel (sell) Likewise, timing “algorithm” takes into account elapsed time, and buying rate compared to other customers etc.

8. New products and services

9. Timely industry info

11. Define proactive from the customer’s perspective What is being proactive? What we think is proactive is actually not. From customer viewpoint: -- Calling everyone is not proactive. -- Calling when they’re not ready is not proactive. Making the call is not necessarily proactive!

12. Accurate predictions bridge the gap between knowledge and action Imagine preparing now for customers with predicted likelihood of buying need next week. That’s proactive. -- Sort customers to call next week. -- Learn about their predicted needs. -- Think and plan what to contact them about.

13. Shifting focus to stage of buying cycle drives cohesiveness of purpose Not: How many calls did you make? Instead: Whom did you call this week? Different purpose for each call Calling Guidance: Shift denominator to whether customer is within or outside buying cycle Too Late Missed Call now Not Ready

14. Re-prioritizing accounts allows new growth to emerge Prune portfolios Keeping gravy accounts can hurt your sales. Give up to get more. - Remove low probability customers who haven’t ordered in a while - Move them from inside sales to web, other cost-effective sales methods - Helps inside sales reps get better experience with better customers

15. Replace “person to call” with “purpose to call” Variety is the spice of… sales - Mix different types of calls - Wards off boredom, builds experience - Blend service, warranty, other call purposes Common theme: call based on predicted buying

16. Prioritize within sales reps’ hours by improving quality of time spent Dealing with trade-offs: Make this call or make that call? When you can predict average order size, reps can call for the $1,000 order first before the $200 order

17. Customers receive less of what they consider “destructive behavior” Sales 2.0, Customer 2.0 and inside sales Think about your customers and analyze their history and buying cycle before you call Use buying cycle to your advantage Call customer precisely when they are needing your call

18. Sustained profitability gains can come from “the other 80%” Reps can focus beyond their best customers on demonstrated evidence of future growth Best created by applying statistical algorithms typically these customers are top of mind other customers are under-served, resulting in lower future value

19. Predictive Analytics as part of the technology suite of enablers Each building block weaves together a story from customer’s perspective Predictive Analytics Technology & CRM Platforms Marketing Automation

20. Predictive analytics provides accurate, tested, scalable content Large volume of data not easy to analyze by reps, and could be redundant/erroneous Feed predictive algorithms to CRM system Push recommendation to sales rep level (versus reports for management) Actions, actions, actions… backed by science

21. Done right, predictive analytics helps support paradigm shift Integrate … with tools and systems already in place; focus on a pressing goal Involve Don’t try it in isolation; involve sales from the beginning Iterate Set baseline and forecast, test, measure, adjust, test, measure...

22. What you can take away Timing calls is not a nice to have; it is critical in the “customer 2.0 buying cycle” Demonstrate value and benefit of shifting to new paradigm and the power of collaboration to gain sales Build a data-driven guidance system for inside sales, using/embedding in CRM; start small and grow

23. Thank You! More at www.valgen.com/blog