What is Predictive Marketing ?

For many years now, companies have been using advanced analysis tools to detect fraud, assess risk and even predict aircraft maintenance requirements in order to reduce flight delays. Using "predictive science" in a marketing context, on the other hand, is a recent phenomenon. The  predictive marketing  which enables us to anticipate changes in a market and forecast consumer purchasing intentions, calls on state-of-the-art tools. But what's the real benefit, and how exactly does it work?

What is Predictive Marketing ?

Predictive marketing is a marketing technique that involves analyzing data to determine which marketing strategies and actions are most likely to succeed. It has developed with the rise of digital marketing, and more particularly e-commerce, which in turn has been boosted by the development of Big Data (massive data processing) and artificial intelligence.

Predictive marketing is fuelled by predictive analysis, a branch of statistical analysis developed in the 1930s. It has enabled mathematicians and computers to calculate and analyze risks of failure and opportunities for success in a wide range of fields, including health, weather forecasting and insurance. In the 90s, as analysis tools became more accessible, marketers such as eBay and Amazon began combining marketing data with algorithms to predict potential consumer buying behavior.

In concrete terms, predictive marketing uses a wealth of data (known as "megadata") linked to consumer behavior, such as web search history and purchase history. It can then assess their future behavior to develop more effective sales strategies, for example by recommending items likely to interest them. It uses artificial intelligence and Machine Mearning to make predictions based on statistics.

Why use predictive marketing ?

• Predictive marketing is first and foremost a powerful sales and advertising tool, enabling companies to anticipate customers' needs and sell their products ahead of the competition. 
• Predictive marketing can save companies money by fine-tuning marketing efforts and eliminating campaigns that don't work with buyers.
• Predictive marketing builds customer loyalty through in-depth knowledge of past purchases, enabling new products to be offered that are perfectly suited to the customer, and new relationships to be created (for example, by sending personalized messages and promotions). 
• Predictive marketing improves the customer experience during the purchasing process, guiding customers and suggesting products that may be of interest to them, without wasting their time. 
• Predictive marketing can increase the size of the shopping basket by encouraging cross-selling (proposing complementary products) or up-selling (recommending higher-end, and therefore higher-priced, products).

How does Predictive Marketing work ?

Predictive marketing works by collecting data from a growing list of sources, consolidating it and combining it with marketing or customer data. This data is used to create a predictive model, customized for each customer.

Amazon's home page, for example, includes personalized recommendations based on each customer's past purchases. The more items a customer buys, the more refined the recommendations become.

Amazon also looks at what these customers have clicked on in the past, the specific types of items they've shown interest in, and the other sites they've visited, also taking into account the time and season in which the purchases were made. This enables them to offer notifications when the customer is most likely to buy. All this information enables Amazon to make very precise recommendations that greatly increase sales.

Predictive marketing also improves customer satisfaction, making them feel as listened to as if they were face-to-face with a salesperson who was very attentive to their needs and desires.

Predictive marketing: examples

For retail sales

Today, retailers are probably the biggest users of predictive analytics applications. Dynamic retail businesses need to constantly monitor customer behavior and market trends in order to adapt to changes and respond quickly with relevant answers. Advanced algorithms analyze market trends and customer buying habits to optimize marketing campaigns, create personalized recommendations and determine optimal stock levels to meet demand.

For your health

A growing number of medical institutions around the world are collecting a wealth of data on patients and their state of health to suggest preventive treatment, predict the results of various treatments, choose the best option for each patient and anticipate the arrival of epidemics.

For financial modeling

Financial planning is an essential part of any business, whatever the sector. Many finance teams are already using predictive analytics to forecast risks and revenues, allocate resources efficiently or optimize operations to avoid additional expenses.

For Human Resources

HR specialists can obtain forecasts of employee performance, turnover rates or the impact of various activities on employee engagement. Aggregated and analyzed data can reveal weak points in human resources management and help managers match the most suitable profiles to each position.

For the Internet of Things

Predictive analysis is closely linked to the Internet of Things (IoT), since this technology collects a vast amount of data that can be analyzed, for example for maintenance purposes. IoT sensors installed on machines continuously collect data on their performance and send it to the processing platform, where predictive models identify anomalies and order parts to be replaced.

For energy

Predictive analytics can help energy utilities create short- and long-term forecasts of energy demand, taking into account weather conditions, seasonality, new consumers and a host of other factors. Predictive maintenance is also an essential tool for the energy industry, as it can reduce equipment breakdowns. As a result, companies avoid unforeseen costs and customers benefit from more stable energy supply services.

Finally, there's the concrete case of Amazon, which has filed a patent for a predictive ordering technology based on the mastery of customer data: it makes it possible to order the products customers want even before they've placed an order !

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