Big Data

Micro-targeting In Big Data: Respect Your Customer

Pinterest LinkedIn Tumblr

Very often I receive mailings, special offers, SMS and phone calls that I do not need and do not correspond to my interests or desires. 

Low-code Application Development Company

Count how many promotional emails per day fall on your email and how many of them are at least a little interesting to you to read them, let alone click on the links. In my case, this is 5 percent, no more.

Each of us rarely thinks about the principle by which we (the recipients) get into this or that mailing group, why exactly we are offered discounted tires when there is no car, medical services under the “health after 60” program – for those in their thirties, hotel rooms in Syzran after traveling in Italy. 

Received an offer – deleted the letter. Received the following – deleted again. Everyone is so used to this that irrelevant advertisements seem to be the norm. We, at Polimatika, operate with somewhat different norms, close to humanism and mutual respect. We will talk about this today.

Companies try to reach as many customers as possible as quickly as possible in order to increase sales, but the conversion of such events is usually deplorable – for thousands of letters, only one can be “point to point” and will provoke the recipient to buy.

Why Do Bulk Distributors Not Work?

Why is this happening? Not understanding customer needs is a road to nowhere. It’s not enough to just bombard people with offers in the expectation that something will work out. 

It is important to realize that another unnecessary letter or call in the morning on a day off will only alienate you from your client a distance beyond the reach of even sales managers with the longest arms. 

Getting into the list of blocked phone numbers or the “spam” folder is guaranteed as a person’s right to privacy of correspondence. By the way, Gmail automatically puts emails in spam if you delete messages from the same sender several times without reading them.

This is where micro-targeting comes in. The thing is extremely useful both for business in general and for increasing customer loyalty and sales, and many marketers have KPIs for retention and repeat purchase, where micro-targeting becomes irreplaceable. 

The method is old and extremely clear – to give the client what he really needs, to create the perfect offer. But, surprisingly, the seemingly classic marketing method reveals its potential when it comes to big data.

Big Data And Policy

Rumor has it that Donald Trump won the 2016 US presidential election solely thanks to micro-targeting and big data. 

Each pillar of his campaign program exactly matched the needs of a specific group of the population: white Americans – racial differences, revolutionaries – a revolt against classical power, youth – slang and communication via Twitter, Latin Americans – separate specific messages for Cubans, Jamaicans, Mexicans and others, villagers – solving the problem with illegal immigrants. Each of the groups received their own very accurate and understandable message. 

This is the case when the analytics of big data of the population of an entire country, coupled with micro-targeting, showed unrivaled effectiveness, and each of the messages hit the bull’s-eye. Brexit, by the way, has a similar story.

The same applies to business – you just need to offer what will be needed, what they will gladly want to buy. But sales are not presidential elections, here it is very important to react as quickly as possible to changes. 

If the fundamental social interests of certain groups of the population may not change throughout life, and the strategy “how to make them vote for me” can be developed without hesitation for a long time, then the desires and interests of consumers of goods and services may change more often than you have time to prepare bases for advertising campaigns. 

I’m exaggerating, of course, but spending more than a month on just one sample of a million customers to prepare a mailing list is overkill. Customer data has become truly “big”

The “Face” Of The Client In The Data About It

Very often, personal data, information from social networks and much more are also used to draw up a complete portrait of a client. Some might call it espionage. The issue is controversial and slippery. 

A couple of years ago, when it became known that Facebook analyzes the private messages of users for targeted advertising (by the way, this is spelled out in the agreement between the service and the user), people stopped feeling their privacy on the network. But we will not touch on this topic. 

Data from social networks for building a portrait of a client is a separate topic of conversation.

The success of any marketing campaign lies in positive customer feedback. If the response is negative or, even worse, bears the character of complete indifference, then this means that you are doing something wrong. 

Well, or you do everything wrong. Trying to understand your client is not an overwhelming task – it is enough to analyze his behavior, interests, past purchases, the quality and quantity of transactions in order to imagine who is in front of us and make the “correct” offer.

I am sure that you have also heard about micro-targeting from social networks, if you have ever placed ads there – select gender, age, country of residence, circle of interests, etc. So, micro-targeting for advertising campaigns in the form of mailings and calls has a similar nature, only the proposals are based on the data that has accumulated over the years of the company’s existence.

Microtargeting For “Kettle”

In one of the videos that we prepared for training in working in the system, you can consider how to form relevant customer groups for a particular advertising offer. You can watch the video tutorial here . 

We took the topic as relevant, but not the most popular – micro-targeting of clients, to whom the cultivator can be offered , because the summer cottage season is ahead. This example eloquently shows that the same can be done with any other product, as long as you have specialists with imagination who are interested in building theories of customer interaction and testing them on big data.

You can target customers by hundreds of parameters and create after dozens of advertising campaigns that will hit the target. 

It all depends on the quality of customer data you already have and how many lines you have. Manually process all records (and there may be hundreds of millions of them) and look for relevant customers – Sisyphean labor, because by the time the advertising campaign is ready to launch, the data selected for it will most likely be irrelevant, and the database will have to be formed again … Wasted time + mailing that won’t work. Sound familiar?

We constantly mention the high speed of data analysis in our system (which we are really very proud of), but in the case of micro-targeting and timely marketing proposal, it is all up to you – how quickly you decide what to offer, who to offer and when to offer. It knows its business, the main thing for you is to understand what you want yourself.


I often come across articles in the press that the importance of Big Data and Data Science is greatly exaggerated, that this is all theory and a bubble. 

Arguing with the ignorant is a thankless job. Big data analysis has long been shown to be effective in all areas. You will be surprised, but data science is not only about Trump and cultivators. State-owned companies use tools to analyze big data, including to improve the lives of the population, and to regulate the work of other organizations. There are a lot of use cases.

Data science has been particularly useful in the commercial field – increasing customer loyalty, increasing sales, increasing conversions, reducing marketing costs (targeted advertising campaigns, mailings, etc.), etc. 

In addition, marketers themselves can work with data, conduct analysis, engage in sampling, and unload prepared lists without the help of analysts or the IT department. 

And all this in a single system, where the data is ordered, understandable and always available to the users of the system. 

Specialists can spend as little as half an hour of working time from the moment the idea appears to getting the desired sample from the customer database. It remains to convey this to the business owners. The benefits of using professional big data tools are too obvious to be overlooked.

You don’t have to go far, our cases with specific results are here .

Micro-targeting combined with big data is a really powerful cocktail. Data can answer any question, help solve business problems, and make your customers happy and you successful. 

Just start building the development strategy of your company not on intuition, but on specific customer data, form for everyone only the necessary and useful proposals, because the key to the success of communication (and especially with customers) is mutual respect.

Has been working in the IT industry for over 10 years. Conducted dozens of successful marketing campaigns focused on direct interaction with clients and studying their behavior.