How to optimize A/B testing in acquisition elements with Lead Scoring

Performing A/B testing permits, among two different versions, to discover which option obtains better results. This is the perfect way to make decisions based on data.

In fact, 60% of companies consider A/B testing a very valuable asset towards conversion rate optimization.

What is A/B testing?

A/B testing consists of a trial-and-error test in which there are two possible options of image, color, acquisition element, text, slogan, offer, etc. in a specific website or landing page.

Both versions are shown randomly to all visitors who land on that website to discover which one from those options is more efficient towards conversion.

AB testing

How to increase conversion in A/B testing with Lead Scoring?

The average landing pages conversion rate is 2.35%. This rate, that could seem low in different terms, becomes common when talking about conversion rate. However, it doesn’t mean that there are not companies that achieve more than that.

How to achieve an increment in that “common” conversion rate? The answer is simple; working towards the main responsible of those conversions: acquisition elements.

A/B testing shows randomly the different available versions to visitors in order to define, overall, the most effective one. But the fact that one strategy obtains better results than other doesn’t mean that it is equally effective to all consumers.

Lead Scoring permits to optimize A/B testing adapting conversion elements to each user according to the actions developed by them within a website, with the objective of sending them to their ideal conversion point.

Segmentation, or clusterization, according to users scoring plays a key role in personalizing their web experience. In relation to each case individually and personalized, not globally and randomly, it is possible to increase conversion rate.

How to optimize investment improving conversion strategies?

Apart from adapting the different acquistion elements to each user, Lead Scoring permits to improve qualifying strategies towards investment optimization, how?

Given that Lead Scoring establishes each lead conversion probability / purchase intention / interest in certain products or services, it is possible to show leads with high purchase probability, those acquisition elements that are more effective, although it entails a higher cost, knowing that the probability of investment optimization is high.

In this way, the most effective strategies will be allocated, not randomly but with well-founded information, to those leads with higher conversion probability.

Let’s give an example:

The actions performed by users within a website determine their scoring percentage; their purchase probability varies along the process. According to that purchase probability, acquisition elements vary to maximize conversion while optimizing investment.


  • User with low conversion probability:


Pepe clicks on a Facebook ad about mobile phone discountsLands on a landing page where he finds more information about the offerA chatbot opens in the landing page and Pepe uses it to get information about the offer


At the moment in which the acquisition element appears, Pepe has 32% purchase probability. This is why a chatbot was shown to him, a low-cost transformation channel that avoids to lose commercial agents time in sales processes with low conversion probability.


  • User with high conversion probability:
Mary researches on Google to get a new mobile phoneClicks on a search and lands on a mobile phone provider websiteMary gets to the same landing page Pepe got toBut, in her case, a telephone number appears and Mary uses it to call and make a purchase

Prior to the purchase, Mary has 72% conversion probability. Taking into account that her purchase intention is high, that same landing page shows a click to call button Mary can use to call; a higher-cost transformation channel but with better conversion rate.

By optimizing your A/B testing in acquisition elements with Lead Scoring, you will be promoting lead conversion besides optimizing investment allocated to them.

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