COVID-19 is all over the news. And rightfully so. All of us here at Bennett Data Science hope that you are well and getting through the hardships as best you can.
I’ve had several conversations over the past few weeks to discuss how various businesses are fairing, given the current state of the world. Reactions to what’s going on are all over the map.
Some of the startups we work with are doing ok, having had distributed teams from the beginning, but comfort levels vary widely from industry to industry and many companies are struggling to understand what the future will bring. E-commerce and delivery services, on the other hand, are set to thrive in the short-term. Amazon alone is looking to hire 100k employees.
One of the big challenges we’re seeing is that A.I.-generated predictions are unable to forecast future events, given current market and customer behavior fluctuations. Predictive models rely on historic data to predict future events. And when this historic data of customer behavior is nothing like what those customers are doing now, we have a problem. Predictions go to rubbish.
Alan Murray from Fortune explains it well:
… modern-day “prediction machines” are often based on data drawn from past behavior. They aren’t prepared to deal with massive shifts in behavior—for instance, when people inexplicably start hoarding toilet paper.
Hence, A.I.-generated predictions are suddenly inaccurate because the models simply cannot predict something they’ve never seen before.
Many different industries are currently impacted by changing data such as extremely long supermarket lines, erratic shopping behavior, and spikes in traffic to sites like public health and financial centers, reporting what appears to be denial-of-service attacks. Companies are seeing signals that, just a few weeks ago, would have been anomalies or outliers. These are the new normal now. And most A.I. is ill-equipped to deal with them.
There is, however, something that can be done.
What can be done
When we think about how to help companies in difficult times, we come back to the fundamentals: companies must engage their customers with products they’ll love. It’s more important now than ever to understand what your customers really want and give it to them when they want it.
You can’t afford to see a drop in customer lifetime value or any of its drivers.
These drivers of lifetime value include:
- Giving customers engaging content and offers when they’re looking for them
- Keeping churn low by identifying patterns that generally lead to churn and using proven churn mitigation tactics
- Delivering personalized marketing messages
These are important fundamentals to get right. But it’s March 2020 and customer preferences around the world are quite literally all over the map.
If you have a business where personalization matters, there are a few changes that will help you retain value from data science:
1. Offer products that reflect the changing preferences of your customers
Your models that use data from six months ago to predict customer preferences are probably not accurate anymore. Instead, train these models on customer preferences from the past two to four weeks. Even though you might not have much sales data, it may give you a more accurate depiction of current customer needs, as the whole world was different six weeks ago. Also, there may be price sensitivity-related changes so be sure you’re accounting for that too before you offer more expensive items.
2. Are you saying the right things? What should you say?
Try new messaging strategies and A/B test everything. If you have an A/B system in place, use it now! What was working before has likely changed.
3. Assess your marketing targets
Take another look at your customer segments. Are they the same or, more likely, have several segments merged into one or two new segments? Knowing this will help you tailor messages in these changing times.
If you do these three things, your company will be far out in front of its competitors.
I believe that willingness to change and adapt will serve us today as much as it ever has, but am convinced that the entrepreneurial spirit will help special companies rise above all the rest and actually thrive as they recognize the changing needs of their customers, and (continue to) exceed their expectations.
Over the course of the last two weeks, we have successfully helped our clients re-strategize and refocus on retaining customer lifetime value using A.I. If this sounds interesting to you too, hit reply and let’s see how we can help your business adapt to big changes in customer preferences and demand.
Here’s to your health and wellness!
The Shocking Correlation Between Quarantine and Domestic Violence
One topic I care about a lot is personal safety. Looking at the numbers, this data scientist discusses how domestic violence rises in times like these. I hope a bit of awareness goes a long way. The article shares some sites and numbers to call for those in need:
Why A.I. Might be the Most Effective Weapon we Have to Fight COVID-19
An A.I. system developed by Chinese tech giant Baidu uses cameras equipped with computer vision and infrared sensors to predict people’s temperatures in public areas. The system can screen up to 200 people per minute and detect their temperature within a range of 0.5 degrees Celsius. The A.I. flags anyone who has a temperature above 37.3 degrees and the technology is now in use in Beijing’s Qinghe Railway Station.
What Have Scientists Learned About COVID-19 and Coronavirus by Using Cruise Ship Data?
Two new studies looking at COVID-19 cases from the Diamond Princess Cruise ship have provided new information about how the virus spreads and the symptoms many people experience when infected. Read more about this here: