So you’ve decided you want to start a web optimisation program. Well done! If you’ve got a website, this is definitely the right direction for you to move in. Being more data-driven with your decision-making can only be of benefit to your business.

While plenty of people made it through 2020 and now 2021 by “ignoring the numbers,” this is never an actually beneficial technique. And if you’re looking for inspiration around experimentation, you can see just a small sample of the results we’ve achieved with our clients at LeanConvert through A/B and multivariate testing here.

As with any new business practice, however, getting set up with experimentation is easier said than done. Below, we’re outlining some of the crucial considerations for you to decide on before diving into experimentation.

Is the Timing Right?

The simple answer is (usually!): yes. It’s almost never the wrong time to start experimenting. If you as a business aren’t A/B testing, you’re either going with your gut (which means you could consistently be making the wrong choices for your customers), or you’re experimenting by looking at numbers after the fact (without a control group). No matter how fine-tuned you feel your instincts may be, they’ll never be as accurate as empirical data.

And if you are just guessing, you’ve already invested time and money into hard coding changes. This after-the-fact approach doesn’t account for seasonality—what if the market happens to pick up just as you launch a feature? The numbers will look positive, but without a proper control group, it’s impossible to draw real conclusions. Effectively, you have no idea what’s really going on with your CX.

Meaningful insights take time to gather, and experimenting allows you to try riskier things that you wouldn’t just implement otherwise. There is an opportunity cost to not having an optimisation program. The longer you take to get started, the longer it takes to start realising value from riskier but well-performing features. Why continue to leave so much unclaimed value on the table?

Any time spent not testing means risking heading further and further in a direction that’s not the right path for your customers.

What Resources Do You Have?

So you’ve figured out your goals for the first quarter of experimentation. Now the question is, how do you get there? This depends largely on the resources you’re working with.

Firstly, one of the obvious cores of a successful optimisation program is the testing tools themselves. Needless to say, there is no “best,” one-size-fits-all solution when it comes to these platforms. Each tool has a unique set of features, strengths, weaknesses—and price points. LeanConvert, as tool-agnostic optimisation specialists, can help navigate the tricky procurement process and find the right tool or set of tools for your specific business. There’s really no other company in the field that can say the same.

It’s all well and good being data-driven in your decisions by A/B testing, but if the tests themselves are not founded in data, you are not giving yourself the best chance of success. Typically, web analytics platforms are used to ask quantitative questions such as where visitors are struggling, or which areas are in most need of optimisation. Pairing this with experiential analytics tools takes you even a step further in understanding your customers.

Whereas traditional web analytics tools primarily give you information about your customer’s end destination—did they convert? How long did it take them to convert? How much did they spend?—experiential analytics provide much more context by focusing on other actions the user took while on your site. Perhaps they visited the FAQ page, or highlighted the product name before leaving your site, signifying that they copy and pasted it into their browser to try to find a better price. Ultimately, these tools bridge the gap between how you planned your CX and how your customers are actually interacting with your site.

Having all four of the aforementioned skill sets can be hard to find. On a small scale, generalists can do this job, albeit usually with limitations. A full-time analyst will have a stronger analytical skill set than someone devoting only 25% of their time to analysis. On a larger scale, it makes sense to have an entire team. At some point, depending on the scale of your business and the volume of traffic available for testing on, there may well be enough demand for four or more full-time team members specialising in these skill sets.

You also need to think realistically about whether you have enough capacity in the business to allocate efforts towards optimisation—bearing in mind that doing optimisation right takes time—time that must be taken away from the other activities that existing team members are performing. If the answer is no, then you should outsource these skills to specialised third parties like LeanConvert. This is the most effective way to scale optimisation in the early stages, whether you want to have our managed service or go in the direction of coaching your internal team.

Who Are Your Main Audiences?

First, let’s take a look at your internal stakeholders. Generally, the more included you make them early on in concept development, the more receptive they will be to the learnings and results as they come in. These stakeholders are also a goldmine of new ideas and helpful feedback, which should be welcomed and sought out frequently. And as mentioned previously, you need senior team members who are actually invested in and excited about optimisation.

Especially when first starting, a good way to get people onside quickly is to find specific problems or pain points that key stakeholders have, for example not being able to get something specific built, or being unable to convince the business that a certain change should be a high priority.

Fix these problems by building something in the testing tool and proving the value of the desired change (or lack thereof, depending on the test results!).

As for the external audience or end-users, you’ll need to determine pretty early on the audiences you need to tap into to achieve your goals. The best tests will address the needs of a specific customer type. Trying to please everyone is all well and good in day-to-day life, but you should not waste time optimising your CX for customers who barely visit your site.

Customer types could be as broad and straightforward as “New Customers” (i.e. a set of goals around first sign up or first purchase), or as complex as specific personas (e.g. female customers who are interested in a specific product category). The point is to understand what your valuable customer segments need in order to perform a valuable action on your site in order to change their behaviour for the better.

In Conclusion

When it comes to starting a testing program for your company, the things you need to consider are; when (the sooner the better), how (depending on your resources), why (in terms of overarching goals), and who for (looking at both internal and external audiences). On top of that, you also need a plan for scalability.

This may feel like a lot to consider—and it is!—but really, the most important thing is to start, and to do it smartly. Start asking the questions above, find the path of least resistance to getting your first test launched, and do not be afraid to reach out for expert support.

Taking the first step is the hardest part, and at LeanConvert we have years of experience helping businesses go from little or no testing activity to wide, multi-brand, multi-national optimisation programs. From guidance on choosing the right tools and personnel, to creating a winning roadmap, to designing and building the first campaign or set of campaigns—there is bound to be a way we can help.

For more information, contact us here.

And welcome to the world of web optimisation!