With increasing revenue coming from online sales of insurance, deepsense.ai’s client was looking for ways to optimize the conversion rate of this sales channel.
In the process of purchasing real estate insurance online, clients fill in numerous fields on a form. This makes the process time-consuming, thus hurting the conversion rate and taking a toll on profits. The company was looking for a way to boost the conversion rate.
deepsense.ai delivered a machine-learning based solution that harvests historical client data and spots the patterns of clients’ preferences and behaviors. With that knowledge, the system delivers real-time offer recommendations in real time, as the potential customer fills out the form.
The second part of the solution leverages data from internal and publicly available databases and connects it with the information provided by the end customer. The model is thus able to predict the features of the real estate that is to be insured. The model also provides information on the state and features of the real estate as well as additional data required to provide an offer and statistics on the building’s location. The solution minimizes the need for the user to make manual changes.
Suggesting information for users reduces the effort they must invest in the process. This vastly reduces the landing page’s bounce rate and boosts the conversion rate.
Moreover, because it leverages information about the client, the solution presents upselling opportunities. It spots clients who may be interested in buying a more sophisticated offer than the most basic ones. The approach can be used to enhance the use of any online form in various market segments.
The parametrization of the insurance package can also function as a tool for recommending insurance features. The proper utilization of information from the form can also aid in modeling pricing. By collecting information about the insurance packages clients query and analyzing how they converge to a buy, the company can better understand what is worth how much money to the client and better price and manage the offer.