It is a fact that purchasing trends are changing from the physical world and personal contact to the online environment. Or at least that's what market and trend studies tell us.
However, achieving this desired conversion factor from an online search to a direct site purchase through the same channel remains a major challenge for any sector due to consumer behavior.
According to Google, 80% of offline shoppers have searched and compared products through online channels before physically going to the establishment where they finally make the purchase, so we can say that there is a change in the buying trend by which the online channel is essential for making the final decision of purchase, but despite this the direct purchase rates for that query remains low.
Furthermore, this effect is particularly significant in the insurance sector, since despite the fact that most companies make large investments in their online channels (web, online rating systems, mobile social marketing applications) the contribution of direct business to the company's portfolio is still not significant.
Understanding the ROPO effect.
The ROPO (Research Online - Purchase Offline) or ROBO (Research Online, Buy Offline) effect or O2S (Online-To-Store) factor is the trend in customer behavior by which consumers perform multiple online searches to get enough information to qualify their decision before making the final purchase decision in a physical location (offline channel).
Measuring this effect allows companies to measure the true ROI of their online campaigns and investments in these media, multiplying their direct conversions with this O2S factor.
That is why insurance companies are making a great effort to simplify the processes of contracting policies to achieve higher conversion rates in the online world. However, the acquisition of a policy for a policyholder is still a procedure by which he/she deposits his/her trust in a company to insure an asset that is of vital importance to him/her.
But even though there are many visits to the channels and online simulations, a large number of customers require direct contact with a sales office to make their final purchase decision. In other words, they need someone "physical" to whom they can turn or who can respond if an incident occurs.
Can we measure the ROPO effect?
Although it is not a simple process since it involves the association of an online search with the final purchase regardless of the channel through which it is performed, there are multiple strategies to be able to relate online searches with online purchases such as
Provide discounts associated with a certain identifier that the customer has to provide when making a purchase in any establishment, request personal data in the search process or customize the product for each potential customer. However, these strategies tend to complicate the online processes and involve a large investment to be able to collect this data in each establishment.
On the other hand, most insurance companies implement strategies to simplify the contracting processes and improve the user experience of their applications to maximize the conversion factor of an online simulation with the contracting of the policy. An example of these strategies is in the implementation of online simulators, whose objective is to provide a price to the customer for the product he is requesting with the minimum possible data.
This tactic that maximizes the online conversion factor produces an undesirable effect if we want to measure the interference of the online channel in the contracting of policies by any other channel (O2S factor). This effect is the anonymisation of the simulations and therefore gives the possibility of directly relating an online simulation to the policy taken out by another channel.
What is the most convenient strategy?
Putting aside the previous examples, the most innovative strategy in this respect consists of carrying out Big Data analysis to relate the information from the simulations with the information from the policies that are contracted through any channel. Through these advanced analyses it is possible to determine with a degree of probability the simulations related to a certain policy and therefore measure the ROPO effect and to be this the first step for the development of an attribution model.
Finally, we can deduce that thanks to this strategy, recruitment processes can be simplified without the need to request personal data from prospective customers, providing greater usability to the online channel and therefore a higher conversion factor or a higher rate of visits and quotes. It should be noted that this simplification of the process does not affect the measurement of the effect since it is based on probability models that allow companies to have mechanisms to measure the true importance of the online channel in the hiring of their new portfolio.
