What is predictive marketing? As competition between brands is increasingly fierce and behavioral data has become abundant, predicting an act of purchase becomes a key element to accelerate consumer conversion and improve the customer experience.

Predictive marketing allows us to anticipate the needs and behaviors of users, and offer them on the spot the products and services that should interest them.

Let’s take a look at what predictive marketing is and how to implement it through concrete examples.

What is Predictive Marketing?

The goal of predictive marketing is to predict the purchase intention of a consumer and personalize the offer to that consumer for products, services, discounts, etc. while he or she is still thinking and has not yet started the purchase process.

Predictive intelligence, in a marketing application, is based on an identical process:

1. Ask a business question about future performance
2. Collect data from different sources (browsing, e-commerce purchases, personal information, etc.)
3. Cross data of existing customers (all latest sales, for example)
4. Use a statistical model to evaluate the future behavior of a client with greater probability. Artificial intelligence can be used for greater precision and more complete information processing.
5. Use machine learning to industrialize the model into “self-learning”.

Why use predictive marketing?

• Anticipate the needs of internet users and reach them before the competitors in a logic of advertising capture of new customers by having a complete optimization of expenses. This improves your return on investment and increases your income.
• To strengthen the relationship with an existing customer through the development of personalized exchanges, knowledge of previous purchases and the recommendation of new products that are perfectly adapted to the customer.
• Overall, to enhance the consumers’ shopping journey by making truly personalized offers that will interest them throughout the shopping process. Certain tasks can be automated to offer even more customization by collecting a large amount of data.
• Create more comprehensive and ambitious sales funnels with smart cross-selling or up-selling.

How does predictive marketing work?

Predictive marketing is fundamentally based on the analysis of behavioral data in very large volumes to anticipate and predict needs. If some very large companies manage to develop and implement their own predictive model, it will be necessary to go to a trusted third party in other cases.

There are several approaches:

• Use Classic Segments: If a person who looks like an existing consumer who bought product X, for example, has not yet bought this product but has similarities (same age group, same interests, same geographic area, etc.), it stands to reason that this person might also be interested in product X. This is what can be called lookalike audiences.

• Exploit Weak Signals: This is a more recent approach that requires an analysis of miles of weak signals (reading an article on a media site, visiting a blog or business site, etc.) by the consumer to determine behavioral harshness and establish an appetite score  on which to make an offer. This approach often uses artificial intelligence and machine learning.

That is what we are doing at Jump Data-Driven Video, a data management platform, designed specifically for video service players to provide our clients with an analysis tool that allows them to improve predictive marketing.

Predictive marketing, examples to remember

Marketing teams can use predictive marketing to personalize the customer experience from A to Z:

• Capture future customers who do not yet know the brand and its products, through personalized advertising campaigns. This is called predictive targeting as opposed to retargeting, which is targeting people who have already visited your brand site.

Here is what we do at Jump Data-Driven Video:

Help clients improve the user experience and get to know them in order to implement predictive marketing strategies directed at users through recommendations and other advertising strategies aimed at users that show similarities to their own.

Internationally, Early Birds, TinyClues, Kameleoon and Target2Sell are the main specialists. Their predictive algorithms bring  the right product and the right content to the targeted consumer, based on browsing data analyzed in real time, making it possible to display your recommendations at all points of contact.

• Pursue the relationship with the visitor or the customer: whether the consumer has made a purchase or a simple click, prolonging the contact in anticipation of their needs with a personalized email or an advertising banner is an effective way not to lose contact and to promote the purchase / buyback

What’s the takeaway on predictive marketing?

Ultimately, predictive marketing is an effective way to develop brand business while respecting the consumer.

Compared to traditional marketing approaches, anticipating a need using the best of today’s technology – artificial intelligence and machine learning – is undoubtedly the future of marketing and in particular  acquisition.