How Kindly’s conversational commerce solutions drove a 17% increase in average order values
Email conversion rate
Onsite message engagement
Increase in onsite AOV
Using Kindly’s conversion optimization solutions, Conrad saw success through higher engagement rates on their website and via email, resulting in a 23% increase in average order value (AOV).
Conrad needed to increase conversions and order value across multiple sites
Conrad.com is a German technological and electronics company. Over the years, Conrad expanded their business throughout Europe and internationally, currently shipping products to more than 210 countries globally. Their huge product range makes Conrad an increasingly popular choice for businesses and consumers alike. The centrepiece of the Conrad brand is their e-commerce experience, which promotes their entire suite of products to shoppers, which is available to shoppers around the world. Since they cater to audiences that speak many different languages, they identified a gap in the level of customer support and website experience they provide. While many people would come to their websites, the traffic to conversion rate was suboptimal for a brand eager to grow. As a result, they connected with Kindly to develop conversion optimization solutions that could provide quality customer support in global markets everywhere. The success was proven through higher engagement rates both on their website and via email, resulting in a 23% increase in average order value (AOV). When Conrad created onsite experiences in multiple markets, they recognized that they needed to tailor their product recommendations and customer support to users who spoke any number of languages. But their customer support team had a finite number of people who collectively spoke only a few languages. Due to their limited number of human resources, Conrad opted for a technological solution that could help them connect with any shopper in any market. They became aware of Kindly’s conversational commerce solutions, and they decided to build a conversational playbook that could be used anywhere around the globe.
Create multiple onsite greetings and messages for different markets
Kindly’s multi language platform is powered by machine learning technology that masters how to respond to customer enquiries as it’s exposed to more support requests. By using AI to infer different languages and learn how to respond in those languages, the platform enables Conrad to provide real-time customer support in the shopper’s language of choice. With a more local approach to messaging, Conrad has happier customers and more loyal customers who make repeat purchases.
Using Kindly’s technology opened doors for new business growth opportunities
Connecting with people on their terms and in their own language of choice increases the likelihood that shoppers will convert into paying customers. Having the means to engage with website users in their own languages enabled Conrad to build direct relationships with shoppers, which helped build a community of brand loyal advocates for Conrad. Ultimately, this created greater potential to scale and grow the business at a global level due to higher conversion rates and more revenue.
Generate recommendations for related products based on past buying behaviors
In addition to learning how to speak in different languages, the machine learning capabilities enable suggestions for related products to offer shoppers as they plan to checkout. The products are recommended based on common purchase behaviors from similar shoppers as well as through add-ons that enhance the value of the initial product. This helps drive purchases of greater monetary value that maximize AOV.
Higher website traffic conversion rates earn more sales and more revenue per transaction
Once the technology was live across multiple domains in the Nordic region, conversion rates increased at the point of checkout across the majority of those domains. The platform was then implemented onto international domains, and the results once again showed higher rates of traffic converted into engaged shoppers and active buyers. Most orders generated higher AOVs, as customer-related accessories and similar products to the initial selected product were added to shopping carts before the completed checkout.