Why Average Statistics is Less Effective than Individual Approach

Why Average Statistics is Less Effective than Individual Approach

In pre-internet time marketing was based on individual approach. Whenit was difficult to get clear statistics and valuable data based on average features, marketers had to take each client as individual.

Today, getting great marketing tools that allows us monitoring statistics and getting data about our clients including their age, gender, location and even more, we’ve learned to create a portrait of an average user what can be useful for our selling strategies.

At the same time, we lost an ability to take each client individually.Detailed analysis showed that portrait of average client is usually less accurate than most marketers think. While we try to catch general features of the great group of people, there are lots of categories of users that have very little in common and sometimes interested in opposite things. When we aim our campaign on so called typical users, we lose around third of our potential clients. It all sounds too pessimistic, right? However, there’s innovative decision that can solve the issue. It’s about replacing your average clients’ portrait with individual analysis of each client.

Individual Approach in Internet Marketing: How it Works

Let’s look back at the time when marketers had fewer tools, no internet and little amount of clients. What did they do? They knew all their loyal clients and could quickly analyze those who appeared in their shop first time. Experienced businessman could quickly decide which client came to spend nothing, which was ready to spend minimal but to come often and which could be a real bingo, spending lots of money in the shop.

Same principles are applicable in offline trade today. However, they appear too unrealistic for internet marketing, right? You may wonder, but it’s far not a problem to aim your adverts at individuals. There are algorithms that will allow you analyzing each client and predicting LTV of each potential consumer.

It may sound too complicated. However, this idea won’t need too much from you. You won’t spend lots of time and, more likely, will notice growth of your income in a very short time.

How Predicted Ltv Helps Your Marketing Strategy

While LTV gives you some statistics data about how much income your clients have already brought to you, PLTV shows how much they can bring to you in future. In the case you start a promo-campaign, it will help to predict most possible results. Knowing your client’s PLV, you can adjust marketing campaigns to be more beneficial.

Let’s have a look at two common and illustrative examples:

  • You are about to start your advertising campaign. It’s targeted on highly interested and active users. You’are about to buy CPI for $2. Quite promising right? Now after checking your users PLTV, you know that in average each user will bring you around $1. That is still not bad, as you aimed your targeting on very motivated users ready to buy your products. However, the campaign won’t bring you any clear income. In opposite, you will lose $1 for each client. This strategy will lead you to great loses, while still appearing attractive and effective. Alternative variant: you predict your potential users’ LTV before starting your campaign and get IDs of those who spends $5 in average. Now, when you target them, you have to pay around $4 for CPI. However, your expensive campaign brings you $1 from each client. See the difference? When second variant appears more expensive and risky, it brings desirable income.
  • You’ve created a great promo to be seen by thousands of internet users. You are about to target your advert on those users who look more like your typical clients. Now you run your promo and prepare to wait for a month to analyze results. Does it work? Surely. However, result of such promos could be highly increased with smarter approach. Now, imagine you can aim your ads at those people who are ready to spend much and are still your targeting group. You shift your spends to hit users with high PLTV and surely, sell more.


Using statistics is always a good idea. However, targeting our clients, we shall look for a way to individualize our statistics data, not to make it more “average”. Detailed targeting may cost more expensive, however, it helps to get more income and loyal clients.

If you are about to run another promo-campaign, predicting paying potential of your users (LTV) is a wise choice. According to marketer’s report, it may result in increasing your income up to 700%.

Are You Ready to Increase AppRanking and Get More Sales?