A Ness client in the retail industry was looking at ways to increase its online sales revenue. The company had a low conversion rate, low average order value, and had little insight into the behaviors of non-logged-in site visitors.
A rapid audit by the Ness Connected Labs team indicated that the core of the problem was not being able to track customer behavior, derive insights, and make personalized recommendations based on those behaviors. We set out to create more precise control for the marketing team by looking at how advanced data analytics and machine learning could help improve the client's customer experience, create engagement, and grow revenue.
The team worked first to Discover the need of the marketers, to understand their business and operational context and their target customers.
With this knowledge we created an innovation brief to empower them and add firepower to their Marketing Technology toolkit.
With this insight, the data whisperers in the Labs team worked with the client data and applied open source machine learning algorithms in order to trigger personalized recommendations.
From there we designed and built a dashboard to surface insights and provide control of the personalization engine for marketers.
The personalization accelerator helps our client go to market faster with its personalization roadmap and enables more effective and precise engagement with its customers – to increase conversions and revenues.
Through better insight into customer behavior patterns, the Ness personalization dashboard enables marketers to track customer behavior and target auto-generated segments with finely-tuned marketing messages. They recommend the right products and content to the right customers at the right time.