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Machine Learning for predictive marketing

How much money can a company earn from a single ad?

That’s the first question every company considers before launching a web, TV or print marketing campaign.
The 2017 Salesforce report on Marketing showed that 60% of French marketing experts are now using AI tools for product recommendation or market maturity prediction.
Tools and techniques to anticipate customer behaviour thanks to collected data, also known as predictive marketing, are now key to help marketing experts make operational decisions. Predictive models allow to quickly identify what makes a good advertisement.

Problems to solve

  • Which marketing channels will be the most efficient to reach this specific customer segment?
  • What is the perfect time to broadcast a video ad on TV in order to reach a customer segment?
  • Can I predict the Return on Investment (ROI) of a marketing campaign?
  • Can I evaluate the optimal budget to spent for a Youtube campaign?
  • Can I anticipate whether a customer is happy to receive an ad of feels harassed?
  • Is it possible to find the perfect mix of marketing channels to reach a customer?
  • Benefits of TADA
    in the Marketing Industry

    Marketing and communication specialists can use predictive models to optimize their campaigns and improve their Return on Investment. However, most of them are not Data Scientists. They usually do not have skills in Machine Learning nor in coding to build predictive models.

    Marketing specialists are domain experts who have accumulated marketing data from their previous campaigns. For an email campaign, they know for each targeted customer whether the email was opened or not and at what time. They usually know the gender, age group of these customers. This kind data is considered Small Data, because it gathers between a few hundreds and a few thousands customer records. Small Data is defined by contrast to Big Data which gathers millions of records. Moreover, Small Data doesn’t work well with traditional Data Science tools and techniques.

    In this context, TADA allows marketing specialists to build predictive models on user behavior in upcoming campaigns. This way, that they can publish the best message possible at the best time on the best channels and get great ROI for their campaigns.
    No data science training is required to use TADA. It is simple to use in a few clicks. Marketing and communication specialists can use their own data without processing them in any way. No need for complicated preprocessing or normalization. Just use your data as they are.

    TADA brings new possibilities for campaign prediction

    With an average of 10% of revenues spent on marketing every year in TV, web and print advertising, it is well worth getting the best return out of such a major investment. Predicting an advertisement’s success based on previous campaigns results can be tricky.

    “Predictive model allows you to optimize a campaign to get the best ROI possible ”

    By using the TADA prediction engine trained on data from previous campaigns, marketing and communication specialists can optimize their choices. They can choose the best channels, the best timing, the best frequencies and blend them together ‘just right’. By doing so, they get the best return on investment on the whole production range and fine tune the best scenarios.
    Such an approach is a precious help to decision-making, especially when marketing specialists must establish priorities between various products and campaigns.