predictive-marketing
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AIBanking industryDataInsurance industrymarketing

This post was written by Lea

Most of the technological trends that are linked with trades revolve around the notion of predictive marketing. We could quote machine learning, marketing automation, big data… The most famous statistical tool, predictive marketing, is increasingly strategic for large accounts that use it to analyze the behavior of their customers. And, if the banking or insurance sector does not escape to this, it is even rather ahead of the subject.

Definition of predictive marketing

As explained by AfterData, a predictive marketing startup and one of our partners: “Predictive marketing is one of the applications of predictive analytics. The latter aims to anticipate certain events and behaviors to accompany, prevent or correct them. It relies on modeling techniques based on data history.

And, while we sometimes have to be careful with buzzwords, “predictive marketing” is not one of them. This is not an ephemeral fashion phenomenon. It’s the opposite! With its many benefits, predictive marketing still has a bright future.

Predictive marketing, the ally of banks and insurance

Revenues, expenses, consumption habits… The sector’s data are a gold mine if they are exploited efficiently. And for that, you have to trust predictive analysis. Its main asset: banking professionals and insurance can address their customers in a more targeted way because they understand them better.

And, more concretely, what are the benefits of predictive marketing for banks and insurance companies?

The right product, the right person, the right time, the right price

Each prospect or customer is exposed to a huge number of advertising messages (+1200/day!). To differentiate themselves, brands must have a perfect knowledge of their ecosystem, and this customer knowledge is based on a large volume of data to analyze. From there comes the customization of offers. Indeed, predictive marketing makes it possible to offer personalized offers, services, and content to meet the different needs of the consumer even before he formulates them. Being able to react in real-time is a real asset for the banking/insurance sector in perpetual evolution, where speed is key. The stake of the predictive in the personalization? Retain higher added-value customer segments, improve pricing and underwriting rates for different contracts.

“I love you, neither I”

Beware of weak signals announcing the upcoming departure of a customer. Thanks to predictive marketing, banking, and insurance players can collect signals of dissatisfaction before it comes to light. Results: they can limit customer attrition, also called “churn“. For example, the “Mutuelle de Poitiers Assurances”, an E-Deal CRM by Efficy customer and user of a predictive marketing platform, can anticipate the termination of a contract, forecast the prospects’ appetite, or refine its sales forecasts.

Better fraud detection

Providing a predictive vision helps identify potential upstream faults before they become real problems. It is active management. Predictive marketing allows banks and insurance companies to identify unusual behaviors or inconsistencies in claims files to detect fraudulent claims. As a result, savings are made and crises are avoided.

Predictive marketing and CRM, two tools that go hand in hand

“The goal is to make life easier for [people in charge, from near and far, of Customer Relationship] by supplementing the standard data of their CRM with information on the palatability of their customers for targeted offers. The challenge is always to better anticipate the needs [of customer] while optimizing the time [of collaborators] “explains Alexis Monier, founder of AfterData and… former colleague of us (proof that CRM and predictive analysis go from a peer!)

Another relevant link between CRM and predictive marketing: machine learning. Indeed, in simple words, machine learning makes it possible to transform big data into efficient data. The quality of the data must be there for these predictions to be the best possible. And many features of the CRM can ensure this quality: deduplication engine, KPIs, purging tool, anonymization, archiving, mandatory fields …

In summary, predictive marketing is a powerful tool that, coupled with CRM, helps you better know your customers to better understand their needs.

AI Banking industry Data Insurance industry marketing