Are you interested in improving customer conversion rates, engagement rates or ancillary revenue? At Rokt, we can help you find out how brands are optimizing the customer experience and increasing:
- Conversion rates by up to 10%
- Social engagement, data or cross-sell campaigns between 100%-300%
- Ancillary revenue 25 fold through the use of third-party sponsors/advertisers
When we hear from businesses about optimizing their ecommerce experience, they tend to tell us how they have tested so much that they don’t think there’s a lot of upside left on the table. Then we go through the user experience and, remarkably, we find many non-performing bits of content to which the user is exposed.
Take a look at this visual to better understand what we mean.
What are some of the challenges with the above?
- In a transactional environment, customers are highly engaged in a linear experience. When you make it hard to get through the experience—with multiple options, extra steps, distractions or ads—you lower engagement, which, in turn, lowers the channel’s effectiveness;
- When you insert other non-native elements into the experience, you also make the site less responsive and therefore less able to adapt to the multitude of different devices consumers are using today;
- If your content remains static, such as when buying an airline ticket and the customer sees the same 10 add-ons every time they transact, engagement drops away over time as repeat customers skip over this content;
- Some objectives are better served in transaction environments than others given the mindset of the consumer. Things that require positive consumer engagement are well-suited to transaction environments. Branding-related activity with formats like display ads and video tend to be a poorer fit for the transaction environment; and,
- The end of the transaction process (i.e., the confirmation page) is one of the most important communication channels in ecommerce. Consumers are still in the same mindset as they were leading up to the purchase and the same learnings apply as in the checkout process. Most brands recognize the value of this engagement point, but very few are using it effectively.
So is there a better way? We think so.
Using what you know about your customer along with machine learning, you can predict what s/he is most likely to engage with during every experience. By optimizing the customer experience and making the transactions native, personalized, and flexible we have found that you can achieve some amazing results.