Customer Smarts Podcast – Using a combination of AI and Behavioural Science to prevent customer loss

Read the Top 7 insights from Customer Smarts podcaster Justin Stafford’s interview with SmartMeasures cofounder.


1. There’s an imbalance towards acquisition vs retention

Up until recently, it’s been hard to track and identify unhappy customers at risk of leaving. So because it’s easier to run campaigns to acquire new customers, many organisations have focussed on building marketing teams and programs around acquiring customers and neglected retaining customers. However, the cost of acquiring a new customer is 5 times higher than the cost of retaining a customer, so things need to change.


2. Customer growth reporting is often inaccurate

As many organisations are very acquisition-focused, they tend to report and focus on “net customer growth”. So rather than separating out the acquisition of new customers vs churned/(leaving customers), they lump it into one number to show that their acquisition efforts are bringing in customers. However, often when large acquisition campaigns are run it also increases customer churn, which shows there is plenty to do from a customer experience perspective.


3. On average 10-30% of customers are at risk of leaving

Companies in general aren’t paying enough attention to their customers at risk. Some companies are leaking or even haemorrhaging customers and then spending 5 times as much to acquire new ones, it doesn’t make sense, it’s massively inefficient.


4. Tracking customers at risk is being done poorly

Firstly, it’s not done frequently enough, it should be done once a week vs once a quarter or even less. Secondly, it’s often done at a persona level, for example customers female 25-35 are at higher risk of leaving, which doesn’t really help you take action. When it should be done at a 1:1 level where you can then try to nurture customers back to being content/happy.


5. Marketing to customers at risk is stupid

Many marketers abuse their email lists, pushing out marketing or sales messages to customers at the wrong time. Doing this to customers at risk is stupid because it may push them over the edge to leave or to even unsubscribe, which means you can no longer send offers. Marketers need to become far more conscious of this.


6. Use AI to identify customers at risk at scale

When you have an enormous customer base, identifying customers at risk of leaving at a 1:1 level is impossible. However, with the AI that SmartMeasures have built it can now be done. Using over 4,000 behavioural variables, it scans through giant customer databases to identify customers who have demonstrated traits that might make them unhappy. The AI is constantly optimising itself to improve accuracy over time.


7. Use behavioural science to nurture customers back

After AI has done the grunt work SmartMeasures uses behavioural science techniques to nurture customers back from the ledge. It’s quite a formidable combination. Which is continually tested and optimised by AI. A very practical use of AI.


Customer Smarts provided the platform and expertise to showcase this example of how SmartMeasures uses this unique combination of AI and behavioural science to manage customer retention better!

You can listen to the full podcast and other enlightening customer-related topics here at Customer Smarts here or on the SmartMeasures YouTube channel here.

We at SmartMeasures are helping our clients by using AI to detect customers at risk, then using behavioural science to nurture those customers back to a happier place. If you would like to know more, get in touch.