You collect data, conduct analytics and make decisions based on it. And that’s a great start, but how can you get even more value out of your data? Predictive analytics allows you to anticipate future events, and not just analyze the past.
Predictive analytics is a data analysis methodology used to predict future events. Marketing today is personalized, contextual and dynamic. Increasingly, its goal is not to attract customers but to understand each user at the level of his desires and the context of consumption. Predictive analytics in this case just helps to predict the very context of the needs and desires of customers and determine the best way to deliver information through physical and digital touchpoints, while building a unique personalized approach.
Predictive analytics is based on artificial intelligence technology. It allows you to analyze a huge amount of data and build predictive models based on it in seconds. With the help of predictive analytics, they optimize prices, plan purchases, develop new products, and prevent customer churn and debt formation.
Attracting more new customers
Attracting customers is becoming more and more difficult – we have a huge selection of online stores and services. In the fight for leads, those companies that can offer their audience an individual approach and real benefits win. How to find out what will interest a particular client?
Based on the accumulated customer data, the customer base is divided into segments depending on preferences, behavior, socio-demographic parameters and financial capabilities. Historical data allows you to build a predictive model and make the most accurate forecast: whether your offer will be of interest to a particular client or not.
Prioritization of leads according to their readiness for a deal is called lead scoring – lead qualification. An excellent example of the use of scoring models is the assessment of the client’s solvency used in banks. The forecast is based on historical data, therefore, if by some characteristics (frequent job changes, for example) you are similar to those who often take loans, forgetting to repay, the probability of failure is quite high.
Predict ad performance
With the help of end-to-end analytics, you can analyze the effectiveness of each advertising channel, and with the help of predictive analytics, you can predict it. If you know what kind of return a particular advertising event will bring, it will be easier for you to plan a budget, turn off ineffective advertising channels or campaigns and launch new ones.
Predictive analytics will identify your customers’ trends in social media, emails, instant messengers, offline events, etc. This will allow you to predict the return on each advertising channel and build a strong omnichannel strategy.
Improve customer experience
Predictive analytics helps not only attract new customers but also improve the customer experience of existing ones with the help of personalized recommendations. For this, the clustering method is used. How does the clustering method work in practice? First, communities of goods are built, which are often bought together.
Product communities are then linked to customer clusters. As a result, we have a forecast: what product, with what degree of probability, and which clusters of buyers can be offered. The simplest example of using clustering: compiling recommendations on the site “people buy… with this product”.