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Companies are struggling
Given the current state of the world, most data scientists and executives agree on the importance of studying recent data to understand how COVID-19 related events have impacted businesses. One such data scientist, Oleg Zero, has stated “The upcoming corona-induced crisis will do the same as any other crisis did. It will sink the heavy and stiff and propel the flexible. From a higher level, reactions to what’s going on are all over the map.”
Some of these companies are doing well, due to having prepared teams to meet these challenges from the start. However, these comfort levels vary drastically depending on the industry, and too many companies are finding it difficult to predict what the future may bring. Other industries, such as delivery services and E-commerce are set to receive large gains, with companies like Amazon slated to hire close to 100,000 new employees.
Unfortunately, there are far more businesses struggling than thriving during these times, and those that are facing hardships must adapt quickly. Reza Sohrabi from StitchFix states as much: “I don’t think there are any businesses that are not impacted by the current pandemic. So, I believe companies have to adapt to the new situation and change gears as to how they do data science.”
One of the big issues we’re facing today during this crisis is unreliable data regarding customer behavior fluctuations. Predictions made by AI algorithms are unable to accurately predict future customer behavior, which means many of the companies that rely on these predictions are walking in the dark. According to Alan Murray from Fortune, “...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.”
Businesses are seeing data that, just a few months prior, would have been considered anomalies to cause alarm. Although this can be considered the new normal now, most current AIs are simply not equipped to deal with them. Fortunately, something can be done about this.
The majority of AI models utilize historical data to predict future behavior. As we can see during these times of COVID-19, consumer behavior can suddenly change. In light of this, companies are starting to see less value in some AI systems as the data provided is no longer applicable when consumer behaviors are changing in such extreme ways.
When we consider ways to help companies during hard times, it’s important to remember the fundamentals. Businesses must provide their customers with goods they love. Now more than ever, it’s critical to understand what your customers truly want and deliver it when they want it. It’s also an excellent time to take a look at how businesses make use of analytics and work with data. Because in the end, the goal of effective analytics is to continually improve customer maintenance and lifetime value. The drivers for lifetime value include:
- Finding patterns that lead to churn and using proven churn mitigation tactics in order to keep churn at a minimum
- Providing appealing offers and content to consumers when they are searching for it
- Providing targeted marketing messaged
These are critical fundamentals to get down. If you have a company that puts focus on personalization, these four steps will assist you in using data science to keep value:
- Dive into the data - Diving into data dashboards is the most important goal for data-driven companies. Do your major assumptions motivated by business goals still hold up? Are these main objectives being supported by incoming data? Have the type of products that people are buying changed drastically? Is there enough inventory? How about your personalization tools, are they still working? If a customer is searching for a new type of product they suddenly want, how difficult is that task?
- Analyze your marketing targets - Have another glance at your customer segments. Have they possibly merged into one or two new segments? Possessing this knowledge will assist you in creating efficient messages during this confusing time. One could even reach out to customers to find out if and how their preferences have changed. The likelihood of them being willing to spend time helping you serve them better is higher with the chance of receiving exciting, personalized opportunities. TrunkClub and StitchFix onboarding are excellent examples of how a business can request large amounts of user information with the promise of a highly tailored experience.
- Offer goods that adapt to the changing preferences of consumers. It’s highly likely that information generated six months ago used to predict customer preferences is no longer viable. Instead, you should be instructing these models to utilize data from the past month or so. There may not be much information there, but it's going to be a more reliable source of current customer needs. You will probably have to do some experimenting with the amount of training data you use, but it will be worth it in the end as you learn where to discard old, inapt data while including newer trends.
- Don’t say the wrong things. Attempt new messaging strategies. The old way of messaging is mostly dead. Few people are buying or behaving the same as just six months ago. As customers desires, concerns, wants, and needs change, your message must also adapt. You can do this by creating a few options for new marketing copy and A/B testing them to see the results. These user segments may have already been previously identified, but they could be drastically different now.
Data is at the center of everything in business, and it’s more vital now than ever. Projections across the world have been alerted due to the unimaginable COVID-19 pandemic. If you are looking for the best way to utilize your data and make it work for you, contact our experts.