Shoppers’ behaviors and consumption patterns tend to change on a regular basis. The types of products that customers flock to today can quickly become obsolete. Instead of trying to find out what attracts consumers at the moment, marketers try to predict their needs in the near future. This allows them to respond in time to their expectations by designing and offering adapted products.
Predictive marketing is therefore an approach aiming at predicting the behavior of buyers. It is based on statistical models fed by Big Data. Thus, all data such as transactions, previous purchases, messages, and GPS signals come into play. Once the data is gathered, the technique consists in analyzing the results in order to propose products or services aligned with the predicted needs.
Which industries are using predictive marketing?
From the automotive industry to telecoms, energy, finance, and insurance: all business areas can use this innovative marketing strategy. But the world of e-commerce is ahead of other sectors.
Data on browsing history is used to determine the preferences of Internet users. The same goes for the number and duration of visits to different pages, as well as the keywords typed into search engines.
After processing the algorithms, e-tailers have a global vision of the needs of customers and prospects. They can also propose complementary products to the expectations already expressed.
Predictive marketing: what about its reliability?
To check if the predictive approach is reliable enough, one should observe the results it has brought in different application projects. Using this type of marketing innovation, the publisher HLi reports its results over a 2-year interval, from 2015 to 2017.
This cloud-based solutions publisher measures its attrition rates, corresponding to the number of unsubscribes compared to the number of subscribers. The statistics reveal a decrease in these rates following the use of predictive marketing.
For this company, the strategy contributes to keeping the loyalty of the consumers. These satisfactory results are not isolated situations but are spread over various areas.
Focus on the pros and cons of predictive marketing
By anticipating your customers’ behaviors through predictive analytics, you can better know them. This allows you to know what products to offer, at what times, and through which channels.
Knowing your customers increase loyalty through your responsiveness and customer satisfaction. You can present complementary products to your customers’ needs, and boost your revenues afterward. Adapting actions to be taken in real-time is also one of the advantages of predictive marketing. All you have to do is pay attention to the results of the learning algorithms.
Although the advantages of this strategy are multiple, its only drawback lies in the collection of data. To work well, Big Data requires a large amount of information. Yet, you must accommodate the GDPR and stay within the bounds of compliance without adopting overly invasive practices.
Should we get into predictive marketing?
Knowing your consumers and adapting to their expectations, saving time for marketing teams, and increasing profitability: there are many reasons to adopt this innovative strategy. But to ensure the effectiveness of predictive marketing, you need to know how to identify the targets, the data to work with and the operations to implement. Calling upon a digital marketing agency in the USA will allow you to walk in the right direction and ensure your success.