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How Can You Improve The Shopping Experience On Your Online Store?

To answer this question, you can draw a parallel with conventional stores. Imagine, upon entering the store, you are greeted by friendly staff who will personally greet you, tell you about the correct combination of shirt and tie, and also inform you about the return conditions if you are in doubt about the right choice. Pleasantly? Conveniently? Is it comfortable? Yes. Think back to your last shopping experience where you felt comfortable, and think about how you could bring that experience online? How would you interact with a user who first came to your site? What exactly would you like to tell him? Where exactly? At what point? How to understand that he even needs to say something? It is the ability to address the right message to the right person at the right time that allows you to create in an online store the shopping experience your site visitors want to experience. And there is such an opportunity now. Personalization provides it. Personalization technologies help to increase relevance, which in turn directly affects conversions, average check, loyalty and engagement. It helps create a personalized shopping experience. The first stage in the mobile game app development company of personalization technologies was product recommendations, which have already proven their effectiveness in terms of increasing conversions and average check.

Now, personalization systems have become something more. With their help, you can individually interact with each user throughout his entire life cycle. For example, to show the visitor of your online store a certain informative message, depending on his behavior on the site and his profile, or make an alluring personal offer at the right time. Used correctly, personalization is a very effective way to boost your bottom line. According to the latest Conversion Rate Optimization Report 2014 by Econsultacy 93% of companies saw an increase in conversions after implementing personalization technologies. Therefore, of course, personalization is a very important and necessary thing for any e-commerce business. This is also confirmed by data from the Consultancy survey. The company surveyed 1,110 e-commerce professionals, including digital marketers, CMOs, e-commerce directors, and CEOs. According to the survey, 94% of respondents say using personalization is critical to success. However, while 72% of executives, although they understand the importance of personalization, do not know how to use it correctly in their online store and what they need for this.

What does it take to optimize the shopping experience for your online store? It's not even about optimization itself, conversion, increase in the average check, etc., but about more fundamental things: how to create a philosophy in your Data-Driven company, what resources you need for this, what team, what tools, what processes should be, and where to start. What is Data-Driven Philosophy? In other words, this is a marketing approach where all your actions are backed up and based on data - qualitative and quantitative. You must constantly analyze and study your audience and find insights (from the English insight - understanding, guess, sudden insight) in web analytics systems. Develop hypotheses for problem solving and test them. Create personal communication with the user throughout his entire life cycle. You need to be agile and flexible, able to adapt to trends and ever-increasing customer demands to create a premium shopping experience in your online store. The key to creating such a philosophy lies in the combination of 4 key elements:

- Correct team

- The right tools

- Correct culture

- Correct processes

Now about each element separately.


Correct command

Perhaps the most important element. After all, the success of any undertaking depends on the team. We are convinced that the right customer experience optimization team must be composed of the following key people:

- An analyst whose duty is to constantly study user behavior and search for interesting insights among millions of numbers from web analytics

- A marketing strategist who is able to build hypotheses based on insights received from a Data analyst and find a reason and an effective solution to each problem found. In addition, the marketer should be the main link between all team members.

A creative designer who knows how to most effectively turn a marketer's hypothesis into reality and knows how to find a creative approach when creating graphic materials.

- A programmer who will help with running complex tests, technical integration, setting up all the necessary tools. Responsible for ensuring that everything works correctly from the technical point of view.


The right tools

To create a Data-Driven philosophy, you should definitely use:

- Web analytics systems, where you will take data on the behavior of your users, find various insights among millions of numbers, on the basis of which hypotheses will be built for subsequent A / B testing.

- A / B testing tools. All results of actions or changes on the site must be clearly measurable - whether they bring real results or not.

- Personalization platforms with which you can create a personal shopping experience in your online store. The personalization platform should be as flexible as possible, with very wide customization and targeting options, in order to create customized solutions specifically for your site.

- Tag Management system. A must-have technology for any modern business. Basically, Tag Management systems are needed for quick and easy integration of third-party codes into the site. But also, for example, it is used to transfer data between the analytics and personalization platform.

- Attribution tools that are used to assess the impact of each advertising channel for a competent reallocation of the budget. When integrating attribution tools, web analytics and advertising sources into one whole, it is possible to set up automatic transmission of bid data to different advertising sources depending on the ROI of each source.


Correct processes

It's important to understand that optimizing the shopping experience, and therefore conversions, is not a one-time process. Success lies precisely in constant work. The optimization process is a continuous cycle with 4 stages:

  1. Collecting data and searching for insights;
  2. Development of hypotheses
  3. Testing hypotheses
  4. Analysis of the results

Collecting Data and Finding Insights

Data is divided into qualitative and quantitative. Quantitative data is the data that you see in web analytics systems: numbers, numbers, numbers. Thanks to them, you can notice that one segment of the audience buys worse than another, which means you need to figure out what is happening and why this is happening. Qualitative data is data that answers the question "Why?" You can get them in only one way - by communicating with your audience by phone, through various polls and feedback systems. People will tell you why they don't buy. Perhaps they could not understand the terms of delivery or return, or the price seemed too high compared to competitors. Perhaps there was some other reason. Based on this data, you can develop hypotheses for solving the problem, which you will test in the future. To collect quantitative data, you first need a fully configured web analytics system, where you must track all key and intermediate metrics. If you are using Google Analytics, you should have fully integrated ecommerce, demographic and interest reporting. You must know exactly at what stage of the sales funnel you are losing your customers, which audience segments are buying better / worse, how people behave on your site, and much more. To collect quality data, you will need customer opinion analytics solutions and feedback systems. Some personalization platforms also have this functionality - and this is a huge advantage. For example, you've noticed that one segment of your audience is buying surprisingly poorly. With the help of such tools, you can ask this particular audience - what's the matter? We assure you that you will learn many new and interesting things that you have not thought of before.

Developing hypotheses

The data obtained will help you notice interesting behavior patterns of customer groups on your site. By interviewing this audience and finding out why they are not buying, you can develop a hypothesis for solving the problem. In other words, you have to ask the question "What if ...?" For example, you see that people from distant regions of the country hardly buy. By asking them direct questions, you can find out that they do not understand the terms of delivery to their distant region. Based on this, you ask yourself the question: “What if for all users from distant regions we add a noticeable message about the terms of delivery to their city. Will this increase conversion? " - this is a hypothesis. We adhere to a strict rule that any testing should be based solely on hypotheses. You can spend tons of time and resources changing button colors, fonts, the size of the text. However, such testing will be meaningless if the basis is not based on a rational hypothesis, supported by weighty arguments. “I think that the blue button will be pressed more often than the green one” is not an adequate hypothesis! Therefore, we strongly advise against conducting meaningless A / B tests that are not supported by any data - they will not affect your profit in any way.

Testing hypotheses

Once you have developed a hypothesis, it's time to test it in action, namely, to conduct A / B testing. To test your hypothesis, you will need a marketer who will handle the entire process, as well as coordinate the work of the designer and the programmer. The designer will deal with the preparation of creative materials; the programmer will set up the test. Also, you will need an A / B testing tool and a personalization tool. Some personalization tools offer built-in A / B testing functionality:

- When testing, use only adequate hypotheses, supported by real data and rational arguments.

- Before starting the test, evaluate the required sample to achieve statistical significance.

- Do not stop the test ahead of time.

- Try not to use multivariate testing and, if possible, do not run many tests in a short period of time.

- Try to confirm A / B tests after a while.

Analysis of the results

After completing the experiment, you should understand whether the implementation of the solution based on the hypothesis affected the key metrics of your online store: average check, transaction rate, percentage of items added to the cart, etc. Of course, the results should be assessed only for the audience segment for which the test was conducted. If the test was successful, and you really noticed an increase in the required metrics, after a while this test should be repeated to confirm the effectiveness of the experiment. Also, be sure to keep a record or wiki. Write down all the tests you have ever run and how they affected your sales performance. Even if the test was unsuccessful and there was no gain, save this information anyway, it will be very useful to you or your colleagues in the future. Further, you need to repeat the whole process over again - collect data, find insights, develop a hypothesis, run a test, analyze performance. And don't be discouraged if at first you don't see any results at all. This takes time and experience. If you run 5 A / B tests and you end up not seeing any difference, that's fine. According to statistics, out of 100 A / B tests conducted, only 13 have a tangible effect. The main thing is to keep working. out of 100 A / B tests performed, only 13 have a measurable effect. The main thing is to keep working. out of 100 A / B tests performed, only 13 have a measurable effect. The main thing is to keep working.


Correct culture

These are happy times for marketers around the world. With the development of technology, it has become incredibly easy and fast to make any changes to the site. You no longer need to wait 3 months for the IT department to launch an A / B test, which after these 3 months will no longer be relevant. The time has come when teams of marketers, analysts, designers and IT specialists no longer clash with each other, but work as one. Technology allows you to remain flexible, even when you are a huge ship with hundreds of people on board. Namely, flexibility and the ability to adapt to changing trends and market reality will allow you to win the competition.

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