Examples of How to Improve Your Customer Experience

What do you do with customers once you get them?  Many times customers are only contacted again at a yearly review or if they have had a problem.  This passive customer experience doesn’t help you improve sales.  Your customers end up with a relationship with a customer service representative instead of you, their salesperson.  Why is that?  Why do we let customers that took blood, sweat, and tears to find and sell, be pushed to the back of our subconscious, never to reemerge? There needs to be a different way. Sales people need to inject themselves into the customer experience.
Predictive analytics allows you to use your data to find hidden patterns inside your customer experience cycle.  Using these patterns you can work smart to reengage current clients at the right time with the right products/services.  This will allow you to close more sales, more profitable sales, and even keep them from going to a competitor.
The following are two examples of how CAN has improved customer experience. We allowed two companies to know which customers were thinking about leaving, and who was ready to buy specific products. We helped both companies gain major insights that improved their sales and customer experience.  They were able to call the right clients at the right time with the right offers.  Here are their stories:

The Bank

Recently we got a call from a bank.  They wanted to start investing in client retention.  They had been focused on acquiring new clients.  However they weren’t making much progress.  Their new accumulation was equal to their attrition.  They were running in place.  This is very common.  People spend a lot of effort on marketing and sales, but they end up losing as many customers as they attract.  This is why focusing on customer experience is so important.
But what to do?  With the use of their own data from their CRM and accounting systems, we gave them the ability to determine when their customers are getting ready to try out a competitor.  We did this by looking at the behavior of clients that have already left and comparing those traits to current clients.  What they ended up with was a list of clients who were exhibiting traits that previously had indicated that customers were getting ready to leave.  Next they developed strategies to renew
If a client is profitable and worth keeping.  They focused on reviving the banks relationship with that client.  For some clients the bank president or personal banker called them, and for others marketing could sent them specific promotions.  However, if the client wasn’t a good client.  They let that client leave without any fuss or mess.  The results was an improve customer experience, customer retention, and improved profitability.
In the process of making calls the bank discovered was able reconnect with their clients, learn about what they wanted in a bank, and what competitors were offering.  In the process of determining if they were getting ready to leave, clients had done research on competing banks.  When asked, the customers gladly told them what they found.  The bank’s own clients did market research and competitive intelligence for them.  Because they liked the bank (they hadn’t left yet), they told them what they did and didn’t like, and told them what they thought they needed to include that other banks had.  Upon implementation of some of the new ideas, retention increased even more.
We helped them see the patterns inherent in cross-purchasing.  They loved the fact that they received a list of people statistically ready to buy a second or third product.  It turns out that there was a definite pattern to second purchases.  Theirs had to do with the number of times they had used a different service of the bank. Once they reached a threshold of different services they had accessed, they moved the rest of their personal banking over to the new bank.
The bank not only improved loyalty, they improved sales. The bank also learned what additional services clients wanted and made their employees happy by providing them information about which clients are worth additional effort and which are not.

The Internet Provider

CAN was contacted by a Internet providers sales manager a few months ago.  She had researched our website and read a few articles online, including “beer and diapers”, “why customer segmentation will improve your marketing”, and “predictive analytics in retail” .  She purchased a loyalty study similar to the banks and then purchased a profitability study to find which clients could be made more profitable. A profitability study finds clients that are exhibiting traits of more profitable clients but have yet to purchase the more profitable product. The Internet provider has plans that cost $55 per month for normal speeds, $72 per month for fast speeds, and $110 per month for really fast speeds.  The Internet provider uses the same fixed infrastructure to deliver each speed.  They had already made the required investments in most cities and neighborhoods.  This meant that most of the additional monthly fee is profit.  Using Pulse we were able to figure out which customers would be most interested in upgrading their service, and would be willing to pay the additional fee.  We provide the company a list of people that statically should be ready to upgrade.  This improved their customer experience, because customers now had the service level that met their needs and resources.  They found that a large percentage of their clients did in fact want the better package, many of them had just never been asked.  Some of them didn’t know there was the better package.
In both cases Pulse helped CAN’s clients provide a better customer experience.  They embraced that there was a better way and improved their profits, sales and their customer experience.  I hope that you have found this post insightful.  Would you like to schedule a demo or stay connected?
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