Predictive analysis tools may help keep customers and increase profits

Many companies, heeding the lure of big data, have rooms and sometimes buildings filled with it. Every transaction with every party they have ever done business with is now in digital form and stored securely.
Some of this data is valueless, but some is quite valuable. With the advance of technology, that customer data is now being turned into usable data that predicts the likelihood of a customer leaving you, lured to another company.
Don MacLennan, co-founder and CEO of Bluenose Analytics, has developed a crystal ball of sorts — with algorithms.
MacLennan says its aim is to grow and retain a company’s customer base.
“By knowing each customer in very specific terms, you can obviously be very purposeful in terms of how you engage them,” MacLennan says.
The operation brings together data from diverse locations within a company.
“It fuses customer data from billing, technical support and customer service as well as internal company reports such as client surveys,” he says. “It aggregates the data and then runs reports indicating which clients are likely to leave when their contract is up and why. This allows the company to intercede and attempt to keep them.”
Practical usage
MacLennan explains predictive analysis by using the example of a cable TV customer service representative.
Using predictive analysis software compatible with most customer relations management tools sends information to the party responsible for customer retention. The representative calls the subscriber, and the conversation, the point of which is to keep the customer, may resemble the following:
Service Rep: Hi. I was just looking at your account as it is expiring shortly and noticed that you never watch the premium movie channels you subscribed to. Is there a problem with your service?
Client: No, I have a smart TV, and I get Hulu Plus, Netflix and Amazon on it. Combined, the cost of all three is less than the premium package price I have with you.
SR: That makes sense to me, but I see for the five years you have been with us, you never had an issue with the service. No outages, no billing errors. Our relationship has been smooth, wouldn’t you agree.
C: That is true.
SR: Any problems with Internet service?” (The representative already knows there has never been a complaint since all customer information is in one place.)
C: No, the Internet is great.
SR: Are you aware that we recently made your connection twice as fast for no added cost — it is best for screening those services you mentioned earlier. It is the quickest connection on the market, and you don’t pay extra for it.”
C: No, I didn’t know that.
SR: Go to the login page for your account and run a speed test. The speed you get is astounding. I can offer you a special price if you renew your subscription now. We can drop the movie channels; and just keep you at the extended basic cable. That reduces your bill by $40 per month.
Digging into the depths
By combining the customer data pertinent information available to the representative, the agent made these points:

  • Needs a faster Internet connection.
  • Does not use premium channels.
  • Called about bill reduction.
  • Never had a service issue in five years.

Those facts came to the customer service or retention specialist and allowed him or her to custom-tailor the pitch to keep the consumer.
“Most vendors in the tech space are very good at getting customers,” MacLennan says. “They use marketing automation programs, sophisticated CRM tools and motivated sales teams to develop their client base. But the ongoing health of these companies depends on retention.

“In reality, customers who seldom or never get in touch with their vendors often do churn. After the customer acquisition phase, companies need a way to learn what signals indicate that clients are satisfied on a consistent basis. Previously, there had been no tools available to help them keep track of how their clients are using their services.”