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Why are contact strategies so difficult?

“I contact my customers every two weeks. Why? I don’t know.”

That’s what an industry leader said to us recently about his team’s digital outreach plan to delinquent accounts.

You can’t grow success on speculation. Shouldn’t there be a better way?

Contact strategy is tough

That leader isn’t alone. Most teams across collections, lending, and servicing have to build their outreach models on little more than guesses.

You've probably got questions like:

  • Which day of the week should I contact my customers?
  • What time of day will get the best response?
  • Which e-mail subject line or text message content is most likely to get an open and click?
  • How often should I reach out to encourage engagement?
  • Are my customers more likely to respond to phone calls, emails, or SMS?

And most importantly,

  • How do I know what is working?

Then you have the complicating factors, like:

  • Regulatory limits on outreach
  • Incorrect or incomplete contact information
  • Staffing limitations, including available hours for responses
  • Stale account prioritization scores
  • Inexperience with digital channels

The guesswork underlying most outreach plans

Companies trying to build a contact strategy often have a process that looks something like this:

  1. Pick an outreach window unlikely to be deemed "inconvenient"
  2. Pick a frequency for contact, such as every other day
  3. Pick a channel or channels to use, such as alternating phone and email
  4. For digital, use basic analytics and UTMs to measure opens and clicks
  5. For voice, look at RPCs and 
  6. Extrapolate from success rates to apply to other accounts

This process has never been better than okay. It relies too much on luck and leaves too many unanswered questions.

What you’re unable to measure

A customer gets an e-mail message. They don’t open it or click on it, but seeing the message in their inbox reminds them to go to the online portal and schedule a payment. 

How can you measure that success?

Agents always dial their assigned accounts in the same order, so a daily call to a specific account always happens between 2:15-2:30 pm, and the customer never answers. 

How can you identify that pattern so you change it?

A customer who has never responded to phone calls or e-mails clicks on a text message. 

Was it the channel, the message, or the timing that worked?

You can schedule text messages to go out at 7:30 pm, but you only have staff available to respond until 8 pm.

Is that enough of a window to allow for response?

What would work better?

Small companies don’t have the analytical resources to devote to trying to answer these questions with any precision.

And even larger companies struggle to find the right data to build models sophisticated enough to answer these questions.

What you need is something fresher. Something that updates after every customer interaction. Something that’s accessible to companies of all sizes.

That hasn’t been possible until the advent of AI. 

But because AI can be trained for expertise on the interactions you have with your customers every day, and because it can learn from every outreach attempt you make, you have a better option.

Learn more about how you can transform your outreach strategy.