Calling Customers: It’s About Timeto Stop Guessing

Parth R. SrinivasaPresident, Valgen

Why get timing right?

How is it a paradigm

shift?

Where does

predictive analytics come in?

Summary: What can

you takeaway?

Session Overview

McKinsey & Co. study finds that:

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

72%“destructive”

Why Get Timing Right?

Fundamental shifts in the sales-customer dialogue

Need for proactive, constant touches that are relevant

“Customer 2.0”, where sales is not engaged until much later in the buying cycle

Convergence of sales and marketing: it’s not just the rep alone

Enabling tools: CRM + Predictive Analytics + Data Driven

Where do you fit in your existing customer’s buying cycle?

Aware Discuss

Share/ Learn

Call

Timing pattern… think traffic pattern

Wait until customer is ready (nurture)

Prioritize, merge (engage)

Move, align message + channel (sell)

Traffic lights have their own “algorithm”… number of vehicles, elapsed time, rate of vehicles etc.

Likewise, timing “algorithm” takes into account elapsed time, and buying rate compared to other customers etc.

So what is nurturing all about?

Reps don’t always have to CALL – can be service, marketing, management; Receptive to hi-touch

Top of mind relevance:- “Customers like you” trends- New products and services- Timely industry info- Follow-up service

How is timing the call paradigm shift?

1. Go from reactive to proactive the way customers see it

2. Give consistent calling guidance to reps, realign their thought process

3. Benefit from social and mobile trends, plus analytics and technology

Define proactive from the customer’s perspectiveWhat 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!

Accurate predictions bridge the gap between knowledge and actionImagine 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.

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

Not Ready

Call now

Missed

Too Late

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

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

Prioritize within sales reps’ hours by improving quality of time spentDealing 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 firstbefore the $200 order

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

Sustained profitability gains can come from “the other 80%”

typically these customers are top of mind

other customers are under-served, resulting in lower future value

Reps can focus beyond their best customers on demonstrated evidence of future growth

Best created by applying statistical algorithms

Predictive Analytics as part of the technology suite of enablers

Predictive AnalyticsTechnology & CRM Platforms

Marketing Automation

Each building block weaves together a story from customer’s perspective

Predictive analytics provides accurate, tested, scalable contentLarge 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

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...

Done right, predictive analytics helps support paradigm shift

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

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