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Why selling insurance through social media remains a challenge


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Data and the various channels it can be gathered from has become the rage in all industries.

In a bid to level up, insurance industries jumped on this bandwagon, too. A few years ago, insurers made an attempt to use social media as a sales channel. However, the experiment failed because social media is a sensitive domain and the usage of its data to assess the eligibility of new applicants wasn’t authorised by Facebook.

There have been other trials and errors. Companies are still attempting to use social media intelligence in a fair manner. But, all in all- using social media as an insurance sales channel still remains a distant reality.

At the root of it, this is because social media can be good for marketing purposes, to raise awareness about the insurance brand, and to start a conversation. However, it is not very fruitful for completing sales.


Why is it a distant reality?


The quality of data

The data collected from social media is both raw and unstructured. It requires a team of specialised data scientists to create predictive models that would be able to predict risk and profile accurately. Converting the data into actionable insights becomes virtually impossible without a customised enterprise platform.

Also, the insurance sales process is detached from social media and a lot of adaption is needed for passing this unstructured data to the CRM for marketing and sales. This adds further complexity to the process.


Privacy laws

We strongly believe in the necessity of privacy laws and the mindful use of available data and information. However, different organisations and industries have different ideas about data privacy.

Social media platforms have a lot of crucial data pertaining to individuals. Third-party members (like insurers) have been interested in leveraging this to better their own services. As privacy laws are stricter for individuals rather the businesses. Insurers can’t yet leverage the individuals’ data from social platforms. Although, it is possible for businesses.

This creates a dissonance between the kind of data required for a truly beneficial insurance process and the data that is currently accessible.


The costly cost of making a handover

Incumbent insurers have grown with complex legacy systems over the decades. Replacing the systems is a costly and time-consuming matter due to the following reasons:

  • The handover requires two systems to communicate and there is no standard API or process around it.
  • It also requires culture change as the marketing team looks after social media, and the underwriting team and IT looks after the system.
  • New teams need to be created with expertise in product, digital marketing, data science, online sales

Thus, the complexity is both technical and cultural. All these reasons wipe out the possibility of any substitution.

In this scenario, the only option that remains is a handover or the distribution of power between social media and insurance legacy systems. This is another complex matter to implement since the technologies are so different.


Thus, instead of outright replacing legacy systems or expending time in managing them with social media, we believe there’s a better approach. It is: augment these systems with flexible solutions like robot process automation (RPA) combined with an intelligent chatbot.



To achieve one’s vision of success, leaping from 0 to 100 is not necessary. Instead, incremental and sustainable steps will create the kind of lasting success that every business dreams of. Spixii solutions can come in and support insurance businesses in both the short and long term to make sustainable changes.

We already know that linking social media platforms with legacy systems is complex due to technology hangups and data privacy. Thus, the need is to find an intermediary- a medium- that can help to connect social media and legacy systems. Spixii intelligent chatbots can fulfil this role.

They are connected to social platforms and allow a handover to secure environments for the execution of complex processes like sales. Not only does this make analysis easier and cost-effective, but it also provides actionable insights about customer behavior.

You can find out more here.

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