By Dan Zimmerman
Businesses in the B2C world have invested heavily in the use of artificial intelligence and machine learning in order to influence buyer loyalty. In fact, Amazon’s recommendation algorithms drive 35% of the retail giant’s sales.
The success of Amazon and other major B2C players has inspired a legion of other tech platforms to bring the power of AI to organizations at a smaller scale. The outcome of which is machine learning as a service (MLaaS). With these technologies and AI software more readily available, the time has come for smaller B2B companies to catch up with their B2C counterparts, commissioning AI initiatives to start influencing their own buyers’ loyalty.
How can AI help B2B companies with buyer loyalty?
Marketers have been moving toward a one-to-one marketing strategy for years, expanding the definition of what’s considered customer loyalty to more of a spectrum, rather than a “yes” or “no” question. With the help of AI tools like MLaaS, B2B companies can inspire deeper loyalty by continuing to market to the individual customer.
At the highest level, AI prediction works like this:
- Identify a goal
- Source and prepare data
- Create models using historical data
- Implement and test the models
- Continuously train the models using results
Predictive models like these can determine which customers are more likely to respond to certain marketing efforts (the goal). Models can reveal answers to questions like, what communication is most effective for certain customers? What time of day is most profitable? What are customers’ browsing behaviors?
With historical data on which marketing efforts have the most impact on satisfaction, organizations can create models using accessible MLaaS products. Once they thoroughly test the model, they can continuously run new customer data through, which both trains the model and produces useful predictions. Ideally, predictions that reveal which customers will respond most positively to specific marketing efforts and become loyal customers.
Data is the key to valuable loyalty insights
The entire AI insights process is less about determining which customers are already loyal, and more about how to predict what will make every customer loyal. Because at the end of the day, marketers want to provide tailored offers for products buyers actually want, not just what they, the business, want to sell — and to do so requires data.
Every piece of data is potentially valuable when building machine learning models. This holds especially true considering that the most important indicator of behavioral loyalty is the frequency and variety of products customers purchased. In addition to these critical data points, things like purchase time of day, geography, communication methods, and product relations are all relevant and helpful data elements for businesses to gather.
You can read the full article on InsideBigData.com.
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