For years businesses have employed historical data to project future outcomes and inform decision making. From detecting credit card fraud to recommending video content, these predictions have typically come from one source of data: operational.
Now businesses have access to experiential data such as customer emotion, sentiment and effort from a myriad of customer interactions at their fingertips. By combining both operational and experiential data, businesses can now make incredibly accurate predictions at scale in order to enhance loyalty, decrease effort and develop the best industry products and services.
Enhance Loyalty With a Deeper Understanding of Customers
Predictive technology helps companies use historical and behavioral data to anticipate decisions their customers will make in the future. By combining transaction history with insights from customer interactions on messaging, phone calls, social media, public forums and more, businesses have a detailed picture of the overall experience and an individual’s likelihood to re-engage with a brand.
With a more nuanced view, companies can make changes to reduce churn and keep customers coming back for more.
Highly specific predictions can also help businesses develop marketing strategies designed to enhance loyalty. For example, ride sharing companies like Lyft and Uber often pair operational data such as ride history with experiential data to determine future behavior. Based on those insights they’re able to identify when and why the individual is likely to churn — perhaps during the summer months when they’re able to walk to work — and then distribute individual promotions such as 50% off rides in the month of June to encourage continued use.
Related Article: 5 Drivers of Personalized Experiences: A Walk Through the AI Food Chain
Create Convenient Customer Experiences
Predictive technology empowers businesses to streamline the customer journey. With a deep understanding of consumer habits and preferences, businesses can take time-consuming and tedious activities like grocery shopping and use data to develop a more personal and convenient experience.
For example, online shoppers today often receive a list of suggested items based on purchase history.
But predictive technology can go even deeper. In addition to transactional data, the addition of customer experience data such as sentiment and emotion, and external data like weather patterns and viral trends can help identify with a great degree of accuracy what an individual might want to purchase next. In the future this will allow ecommerce companies to shop for their consumers, conveniently delivering products to their doorstep and ensuring they only have to return fewer items.
Related Article: A Pragmatic View of Predictive Analytics
Delight Customers With New Products and Services
In addition to creating exceptional customer experiences, businesses need to have a pulse on consumer preferences to develop desirable new products and services. By listening to and analyzing customer feedback, companies are now able to better identify what consumers are in the mood for and can develop a roadmap accordingly. Because the roadmap is informed by Voice of the Customer data, businesses will dramatically improve their chances of success by bringing to market the products and services they know will be well received in the market.
One example is Ben & Jerry’s. The company is famous for crowdsourcing future ice cream flavors with customers and by mining social media data. Its famous “Do the World a Flavor” campaign quite literally asked customers to create a flavor by presenting a fun, interactive game. The company combined customer answers with historical data and the likelihood of flavors and names to go viral to create its next best sellers. This type of analysis reduces superfluous brand spending and allows companies to develop new products with increased confidence.
Predictive technology is as close to looking into a crystal ball as businesses can get. The analysis of both operational and experiential data provides companies with highly specific insights into consumer behavior to build brand affinity, create convenient experiences and develop products that will be met with high demand. As the economy becomes increasingly centered around personalized and positive brand interactions, investing in predictive technology will provide a crucial competitive advantage.
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