What is your company’s approach to conversion rate optimization? Maybe you’re like most — running a few ineffective tests that start and stop and produce forgettable results. Sure, you may have determined that the blue button is better, but what value is that information actually providing?
Here’s the honest truth. Traditional testing just isn’t good enough anymore because there’s too large a gap between your ideas and your ability to harvest gains from those ideas. Worse, traditional testing doesn’t help optimize the entire customer journey.
Consumers today are interacting with your brand in more ways than you can imagine, whether that’s through your website, mobile app, social media, or products and services. If you want to compete in this fierce retail environment, you need to develop a strategy that focuses on optimizing every step of the customer journey. And today, the only way to do that with any measure of success is to start prioritizing full funnel optimization.
Before you rush out and start optimizing everything, we recommend you consider the following factors and how they are impacting your full funnel experiences.
It’s important to understand the products and services you’re selling when it comes to creating an effective experimentation and optimization strategy. We recommend that you know the answers to the following questions.
Your experience optimization strategy depends heavily on how many SKUs you are tracking. The more SKUs, the harder it is to keep up with A/B testing.
Traditional A/B and multivariate testing methodologies have limitations because each experiment may last several months and provide results that are only valid for a short time. Manually replicating these experiments over thousands of SKUs is an impossible task.
An ML-powered optimization solution is more effective regardless of your number of SKUs. It can perform multiple experiments simultaneously at scale.
The effectiveness of your experiments will depend on the level of traffic that your website and app receive.
You need the right amount of traffic for your experiments to be worthwhile. Larger sample sizes offer more meaningful results because they allow you to achieve some degree of statistical significance.
If your website doesn’t have enough traffic, your experiments may produce unreliable results and strategies that could damage the customer experience.
No two customers are exactly alike. For instance, a new customer will likely interact with your website, while one familiar with your brand may download your mobile app or look through your social media pages. You must optimize for all of these touchpoints.
One thing to keep in mind is that retaining existing customers is often cheaper than obtaining new ones, but new customers are more likely to become loyal.
Of course, these same new users are more likely to abandon your website if it isn’t optimized properly. To maximize the effectiveness of your optimization strategy, remember to focus on optimizing all aspects of the customer experience, not just one.
Why does a visitor look at a brand’s website initially? The most common reason is to learn about the company’s offerings and to compare them to others on the market. Make sure that your strategy caters to the Compare, Collect, and Choice model.
Ask yourself what the goals of your potential customers are. They could be simply finding the best product for a specific price, looking for an eco-friendly alternative to something they already use, or solving a specific problem.
The development of effective customer experiences always involves analyzing the goals and preferences of your customers, before running a single experiment. Understanding your audience demographics (age, gender, income levels, etc.) goes a long way to addressing their needs.
What are you doing to optimize your customer experiences? Traditional A/B/n testing just isn’t sufficient anymore. While this may help you generate some insights, an ML-based approach is necessary if you want to optimize at scale, and do so continuously.
Not sure where to start? Download our retail ebook, Don’t Delay, Optimize Today!, to find out how you can approach customer experience optimization in a retail environment, what strategies work, how you should approach experimentation, and what not to do.