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Winning Back Lost Customers

From the March 2016 Issue

For any service company that bills on a recurring basis, a key variable is the

rate of churn: How many customers cancel? In many competitive industries, churn

can be substantial some wireless carriers, for instance, lose 3% of subscribers

each month. (Other businesses plagued by churn include insurance companies,

gyms, and online streaming services.) Companies with high churn typically spend

vast sums on marketing to try to replace all those defectors. New research

shows that they might be better served by smart strategies aimed at getting

lost customers to come back to the fold.

V. Kumar, a marketing professor at Georgia State University who studies win

back strategies, cites three reasons companies should focus more energy on

lapsed customers. First, these people have demonstrated a need for the service,

making them far better prospects than random names on a cold-call list. Second,

they are familiar with the company, eliminating the need to create brand

awareness and educate them about the offering and thus reducing the cost of

marketing to them. Third and most important, recent technology, particularly

more-sophisticated customer databases, allows companies to draw on information

about how people used their service the first time around to craft

more-successful win-back offers and to identify and go after the most

profitable defectors.

Pitching the Right Offer

A telecom firm tested four win-back offers with 40,000 customers, looking not

only at which offer lured back the most people but also at which was the most

profitable.

Strategy Per-Person Cost Success Rate ROI

DISCOUNT OFFER:

$20 off for 6 months $120 45% 668%

UPGRADE OFFER:

A $35 movie channel free for 3 months $105 41% 793%

BUNDLED OFFER:

$20 off for 6 months, plus a $35 movie channel free for 3 months $225 47% 302%

TAILORED OFFER:

Customers who left over price get the discount; customers who left over service

get the upgrade. $120/$105 45% 596%

From Winning Back Lost Customers, March 2016 HBR.ORG

Kumar and two colleagues studied data on more than 53,000 customers who left a

telecom company over a seven-year period. To help focus the firm s ongoing

efforts to win such people back, they examined how each lost customer behaved

before canceling, why each canceled (many companies ask departing customers

this question), how each responded to various win-back offers, and how

profitable each one who signed on again subsequently became. As they parsed the

data, they sought to answer four questions.

How likely is a given customer to come back?

Many companies try to regain every lost customer, but this can sap marketing

dollars; firms will be more efficient if they focus on people whose prior

behavior suggests a predisposition to return. The researchers found that

customers who have referred others, who have never complained, or who have had

complaints that were satisfactorily resolved are the best bets. Reasons for

leaving are also predictive: Customers who canceled because of price are more

likely to come back than those who left because of poor service, and people who

cited both reasons for quitting are the least likely of all to return.

Kumar visited telecom companies around the world to explore their win-back

strategies and found that many are experimenting with propensity models like

this one. But few are investigating which customers would be most valuable to

win back the issue addressed by the following questions.

There s an Art and a Science to This

Cox Communications, the third-largest U.S. cable provider, plays in a

high-churn industry where win-back strategies are vital. HBR recently spoke

with Mark Greatrex, Cox s chief marketing and sales officer, about the company

s evolving efforts to woo back defectors. Edited excerpts follow.

How have your win-back strategies changed?

There s more sophistication in the analytics we re doing around individual

customers and what their experience was with us the first time around. We can

now do personalized marketing at scale customizing the message, the offer, the

pricing. And we have new services, such as one-gigabit internet speeds and home

automation and security systems, that give lost customers a reason to take a

second look. People are more likely to come back if we improve the value

proposition. Win-back is definitely becoming more important and we re getting

better at it.

How do you decide what to offer lost customers?

By understanding why a particular household left us, we can pick up the thread

and respond. This doesn t just help with win-back we also have a pretty

sophisticated retention program, and as we capture information about why

customers intend to leave, we use real-time decision engines to inform the

conversation and try to keep them with us. There s an art and a science to this

it s not just math. It requires inventiveness and creative flair.

Has this work changed how you deal with customers who haven t left?

Yes. The analytics that guide our win-back efforts have helped us better

understand the customer experience. For instance, we re more mindful of certain

trigger points in a customer s first life with us such as the time when someone

rolls off an introductory discount. We pay very close attention during those

moments, because we re aware of the economics of retaining customers versus

having to win them back.

How long will a reacquired customer stay, and how much will he or she spend?

There s little point in wooing back someone who will depart again a few months

later, so it s useful to predict how long a returnee will stay on board. The

researchers expected that consumers who bolted once would depart quickly during

their second stint. In fact they generally stayed longer, and customers who

defected because of price behavior suggestive of fickle deal seekers stayed the

longest of all. Second-time customers in the study had an average lifetime

value of $1,410, versus just $1,262 during their initial run with the service

highlighting an important upside of win-back strategies.

Which people should get which offers?

Many firms have one-size-fits-all incentives. The telecom firm targeted 40,000

lapsed customers whose prior behavior indicated they were likely to return and,

with help from the researchers, tested four inducements on them. One group was

offered a discount. One could get a service upgrade, such as a free premium

cable channel. One could get a discount and an upgrade. And members of one

received offers tailored to their reasons for leaving a customer who defected

because of price was offered a discount, while someone who canceled because of

poor service was offered an upgrade. The bundled offer yielded the highest

win-back rate (47%), followed by the tailored offer and the stand-alone

discount offer (both 45%). The stand-alone upgrade offer yielded a 41% win-back

rate.

Which win-back strategy is the most profitable?

Knowing what kinds of offers lure back the most customers isn t enough; the

costs and returns of each are important too. Although a service upgrade has the

lowest success rate, it s the cheapest strategy and has the highest return on

investment. And while the bundled offer has the highest success rate, it also

has the highest cost and the lowest ROI. Kumar notes that companies don t

always choose the strategy that will maximize profit, because many are in

industries where market share is paramount. For most companies with

subscription models, he says, Wall Street rewards the acquisition rate how

many customers did you add this quarter? rather than how much money you made

from those customers. Kumar sees this as shortsighted, but it explains why

firms might utilize the strategy most likely to attract the largest number of

returning customers, even at the expense of profit.

Many companies have a lot to learn about bringing back lost customers. Simply

identifying those who are the most likely to sign up again, rather than

appealing to every defector, can increase win-back rates eightfold. And a large

company with multiple product lines, such as a telecom providing landline,

cable, wireless, and home security services, can benefit from

more-sophisticated ways of analyzing customer behavior to offer enticing

bundles. Too many companies go after whoever they ve lost, throwing all these

offers at them, hoping something will work, Kumar says. I hope this study

helps change the way they operate.

About the Research: Regaining Lost Customers: The Predictive Power of

First-Lifetime Behavior, the Reason for Defection, and the Nature of the

Win-Back Offer, by V. Kumar, Yashoda Bhagwat, and Xi (Alan) Zhang (Journal of

Marketing, July 2015)

A version of this article appeared in the March 2016 issue (pp.22 23) of

Harvard Business Review.