A good business is able to give its customers what they ask for. Through the creation of a research channel with all necessary filters. But a large company must always be one step ahead. Steve Jobs said: “Customers do not know what they want until we showed it to them!”. This is exactly the basic concept of predictive marketing. The average customer tends to focus on things he already knows. He usually relies on a provider who already knows, to get new ideas about what he might like. However, companies are called upon to break this cycle. Trying to serve potential customers as quickly as possible, thanks to technology.

Predictive Marketing: the role of data

The current trend in customer loyalty is all based on creating experiences. It should personalize the relationship with consumers trying to find out their preferences and acting accordingly. At the same time, you also need to maintain high safety standards for privacy. In this context, the role of data is essential.

An invaluable predictive Marketing lesson was given to us from Amazon. This company, based on the products selected by users, has been able to create a hint system that led to a sales increase of 35%.

Obviously, not all businesses can count among the ranks of its employees to an army of developers and engineers. But to achieve good results, you can also rely on simple and free plugins. With a potential increase in sales of 15-20%.

The recommendation engines: how do they work?

The data collection is gasoline so-called recommendation engines. That the suggestions sent to users as they browse in search of a product.

To understand how the recommendation engine plays, the heart of predictive marketing, we can think of the activity carried out by a librarian.

If you assiduously frequent the library of your neighborhood, the librarian knows you personally and he also knows, every time, suggest a good book according to your tastes. If you just moved and brought into a certain library for the first time, the librarian will eventually recommend a generic best-seller, not knowing you.

The content-based filtering

The basic technique of the recommendation engine is filtering based on content. In essence, the company will take advantage of a system based on an algorithm, from the initial search, to include in the results all that relevant to your product. Taking advantage of the tags.

The benefit of this solution is obvious: it will take much less time to learn a user’s preferences, although again.

The alternative is the collaborative filtering, which takes into account the preferences of other users who have already purchased a particular product.

What is certain, as being said before, is that to work best, this system needs to work on a lot of data. More elaborates, more people are able to achieve and the needs will be met. With the resulting increase in sales and popularity of your brand.

Possible problems

If your company has recently opened, or if you have only recently started to devote to predictive marketing, it will take a bit ‘of time before the system starts to give significant results. This is a normal stage, defined by experts“cold start”. Even the giant Netflix is past.

Paradoxically, the biggest trap of an engine of recommendations may be its fine-tuning. That filtering that can put off unwanted products and sometimes harmful.

Another possible problem could be the so-called Snowballing effect. Once a product acquires a certain popularity, it can be presented several times at the expense of other equally viable products.

Predictive Marketing, through the development of ever more efficient solutions, is undoubtedly the future as regards customer loyalty. Both for the sale of products, both for the supply of services.

Always in tune with the times, Gruppo La Meridiana can help you find the best solutions for your business. Contact us today!