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Tools & Techniques for Improving Conversion Rates

Tools & techniques for improving Conversion Rates

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Category : Blogs

Anyone who has kept up with my blogs will know that two things are true about me:

  1. I’m a technophile, who can never have too many gadgets  (much to my partner’s irritation)
  2. I believe that, in business, siloed data is detrimental (if not fatal) to an organisation ever achieving its goals. To me, there is no greater business blunder than keeping your data sets in isolation.

I know that referring to yourself in the third person is never a good thing, but this guy said it years ago:

“By bringing together web analytics and other internal transactional data, we paint for ourselves a great picture of what has happened in any given journey across various sites and channels. With a well-planned and structured set of unique identifiers, you can also merge Voice of Customer data with data from web analytics and BI. Doing this allows you to understand why these journeys are not always performing as expected. You can then be guided by the customers themselves on how to improve the customer experiences at each touch point.”

Nick Willis, Business Intelligence Meets Web Analytics: Breaking down the silos, 2013, p35

What have the silos got to do with conversion rate optimisation?

To my mind: everything.

The work that we do at Station10 repeatedly proves that the most effective programmes are always customer focused. At the end of the day, conversion rate optimisation is all about understanding what your customers are doing and why to help you effectively interact with them across any channel or device.

Knowledge is power

Station10 deals in customer insight. Put simply, we take the data that you have and use it to tell you things you didn’t know about your customers, and how they interact with you, across each of your channels. Armed with this knowledge, you can make suitable adjustments to increase the rate of customer conversation.

Of course, if you want to influence a consumer’s buying behavior you need a good understanding of their current position. How can you optimise an online experience for them without knowing their opinions and movements well? You can’t hope to influence their next steps without a good idea of where they are now.

One of the many issues I have with a/b testing and other ‘simple’ methods of improving site performance is that they look at optimising one ‘thing’ against one measure.

Human’s are not that 2-dimensional.

How often is a customers’ decision to purchase or not to purchase swayed by one individual thing (other than price!). The reality is that no-one is that easily manipulated. What’s more, by optimising single elements across the board those improvements become unfocused, and therefore, ineffective.

Get personal

This is where personalisation and targeting can help. How each customer reacts to each element that you test is vital to optimisating an experience for them. But you need a strong understanding of your ‘known’ customers and to have outlined good profiles for your ‘anonymous’ visitors, in order to truly asses your individual customer’s responses.

This is where the Silos will kill you.

If you know your customers well, you can segment them effectively into likeminded groups. With this information in place, you can then reap much larger rewards from your a/b testing programmes.

Group X, who often behave in this way, reacted like this and like that. We now know that if we do this, we can make that happen….

By targeting your investigations, you make each test more relevant and your optimisation project will resonate with its audience more effectively.

Track performance

Of course, as is always the case with data, there is even more to gain. Having all of this data in one place, to generate a single customer view, allows you to measure your performance more holistically.

If you’re operating a ‘simple’ test that is untargeted, and therefore measuring performance against one indicator, you will often find that results can be misleading.

Results might be broadly positive, but negatively effect customer engagement as a whole. i.e. a test may lead to more ‘adds to baskets’, but lowers basket values. Very little has been gained here, but you might never know.

The more data you have to work with the better. If you have a single customer view, gleaned from data collected from multiple sources, a more holistic set of performance indicators can be analysed and reported.

Better together

Only by getting all of your data in one place, will you be able to capitalise on the intelligence that can be gleaned from it. Once you are working with all the information that you have at your disposal, then can you use it to influence your consumers.

In any optimisation programme, you must know your customer closely if are to influence buying decisions and increase the rate of conversation. Knowledge is power (or so they say), and it’s the data that arms us with that authority.

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