You’re probably starting to hear terms like “predictive marketing” or “predictive analytics” more and more often.

We are going to explain to you in a very simple way what predictive marketing is all about:

1.Definition of Predictive Marketing:

Predictive Marketing consists on the use of a series of statistical techniques that analyze current and past data in order to make future predictions or detect unknown events or situations.

Therefore we are talking about applying Data Science to make better decisions, predicting which of the actions that we are going to launch are going to be successful.

That is, it analyzes a volume of important data, it applies algorithms to understand and learn based on that data, in order to be able to predict “something”.

Applied to marketing, predictive marketing is to analyze the behavior of users in order to predict whether they will end up performing an action, usually a purchase.

2. How to do Predictive Marketing?

To do Predictive Marketing you need several steps:

  1. Data Collection
  2. Organization of this data
  3. Application of Predictive Algorithms
  4. Drawing Conclusions
  5. Application of Conclusions

To find out about predictive marketing you can start from the Wikipedia documentation.

One of the most useful parts of predictive marketing is being able to detect from the traffic that is visiting us, who really has the intention to buy:

predictive-analytics

In this case we are analyzing users behavior to predict who intends to buy. In other words, analyzing user behavior within the site, such as consulted pages, speed, days, hours, devices, traffic sources,…. the objective is to know who wants to buy and who is browsing.

In the image you can see how:

  • Traffic has been divided into 6 segments from A to F. Where A are users who want to buy once and F users who are just browsing. Blue Column.
  • Green column: how sales have been distributed by each segment A, B,… F

We can see how 60% (A+B) of sales come from 4% of the traffic (A+B)

3. Predictive Marketing Use Cases

1.Improve the Quality of Call Center Leads

For example, by applying predictive marketing we can predict whether the leads we are capturing from Marketing for the Sales department correspond to people who are really interested in buying.

We have studies where we see that 16% of leads generate 84% of turnover

Besides, the practical use is incredible. Alerts can be created so that when a Lead A, is visiting the site, they send an alert to the sales team.

2. Launch Marketing Campaigns according to the user’s purchase intention

“Half the money I spend on advertising is wasted; the trouble is I don’t know which half”

John Wanamaker

This sentence by John Wannamaker is totally obsolete thanks to predictive marketing

If we know if users want to buy or not, we can set up marketing campaigns aimed at users who want to buy “Buyer Intent Campaigns”, adapting the message, the landing… Vs other very different campaigns for users who do not want to buy. For example, if a user does not want to buy, why are we going to show him messages of “buy, buy,…” it would be better to launch messages so that he feels comfortable and “comes closer to making the decision to buy”.

4. Predictive Marketing Course

We have developed a Predictive Marketing Course, very simple and powerful, where we explain Use Cases.

It is a first glance at predictive marketing and we explain in detail how to get started with our predictive marketing tool.

5. Predictive Analytics Tools

  1. Adinton: Predictive Marketing and Attribution Modeling Tool.

2. Other Tools: 6sense, infer, Madkudu

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