In 2001, Gartner proposed the following definition of big data, “Big data is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.” Thus, the three main properties of big data include high-volume, high-velocity and high-variety. Simply put, big data indicates vast and complex datasets taken, as a rule, from non-standard sources. These datasets are so large that traditional programs cannot process them. Simultaneously, business people can use big data to solve problems that previously seemed too complex.

Big data sources can include:

• Internet (social networks, blogs, media, forums, websites, Internet of Things (IoT);
• corporate information (transactions, archives, databases and file storages);
• Devices (sensors, recorders, and more).

No wonder that big data is the basis of the insurance business. Just imagine: the whole insurance business is entirely based on information: statistics, information about customers, insured events, the likelihood of their occurrence, and the financial assessment of all this data. Other than that, marketers use big data in insurance for attracting new clients and boosting sales. This article will describe how big data is used in marketing, in particular by insurance companies.

Why is big data important for marketing?

Using big data for marketing purposes is a marketer’s secret weapon, which is something at FDL we have experienced first hand. By itself, the data is practically useless. Its value becomes evident in the ideas obtained based on the data analysis, the decisions made, and the actions performed. Using big data in marketing helps you achieve multiple goals:

1. Attract new customers. Big data will help you understand who your customers are and where they are located, what they want, and even the best time to contact them.
2. Win more leads with sales intelligence, i.e. a wide range of technologies that help salespeople find, monitor, understand information on prospects’ and existing clients’ daily business, and as a result, grow the company’s sales.
3. Increase existing customers’ loyalty. Big data will let you know what influences your customer’s loyalty and what makes them return to your company’s services again and again.
4. Optimize marketing. With big data, it is easier to determine the optimal marketing costs across several channels and improve marketing programs through their testing and analysis continuously.
5. Make online reputation management more productive and less time-consuming. Through big data analytics, organizations can find millions of online reviews, social media posts, online interactions, and specific mentions and learn what their clients think about their services and products.

How insurance companies use big data?

It’s worth noting that insurance companies use big data not only for marketing purposes. As we’ve already pointed out, data is the basis of any insurance service. Thus, big data is essential for:

• personalization of insurance cards;
• risk assessment while forming insurance rates;
• prevention of insured events;
• anti-fraud;
• automation of routine processes and operations.

Big data usage in the insurance business is vitally important since all the decisions are made according to the previous history and various input data.

Big data in insurance marketing

1. Personalisation of insurance offers

The modern consumer doesn’t want to be a faceless unit of the target audience. Instead, the client needs the offers only for those products that they are interested in. An insurance company can offer a suitable insurance product by analysing information about potential customers’ behaviour. For example, if a person is interested in hotels and flight schedules, they probably need travel insurance. At the same time, people looking through real estate ads may be interested in property insurance services. It’s essential to point out that web scraping in insurance marketing plays an important role when marketers gather big data about the brand’s potential customers. Web scraping allows collecting any data from an abundance of online resources, providing marketing specialists with up-to-date information about consumers’ preferences and interests.

2. Building brand awareness

Working with big data is one of the requirements for successful brand promotion today. According to the Aberdeen Group study, retailers using big data increase brand awareness by 20.1% annually, while those who do not use it – by just 7.4%. Insurance companies don’t neglect using big data when it comes to increasing brand awareness. It combines various strategies based on big data usage (CRM, SEO, analysis of website visitors’ behaviour, statistics, etc.). Additionally, it allows marketers to place content (blog posts, target ads on social networks, banners) when a potential client can notice it.

3. Staying relevant and up-to-date

Real-time data analysis allows insurance companies to quickly detect and respond to the slightest changes in consumers’ behaviour. If the information background and consumers’ behaviour change, insurance marketers will miss new advertising opportunities. For example, according to the Edelman Trust Barometer’s research, at least 77% of respondents expected brands to emphasize the problematic situation in which the target audience was in the companies’ ads during the pandemic. The majority of respondents (83%) demanded that brands somehow demonstrate their involvement, and 57% urged to be careful with humour. Surely, insurance companies couldn’t turn a blind eye to such changes in the clients’ behaviour and expectations.

4. Collecting clients’ feedback

Big data allows insurance companies to efficiently process direct and indirect feedback from their existing and potential customers. As you know, a customer can leave feedback on any platform, including some survey or questionnaire, comments on social networks, reviews on forums and so on. Thanks to gathering big data from this range of online resources, insurance companies get a clear picture of their customers’ perception of the brand and its services.

5. Analysing competitors’ offers

Like any other business, insurance companies use big data for competitors’ analysis. It helps them understand their own services’ weaknesses and strengths and implement new offers to attract new customers.

6. Estimating ads’ effectiveness

Online-to-offline (or O2O) is another new tool developed thanks to big data. It is an approach that allows tracking the clients’ offline purchases after an online marketing campaign. Analysing vast amounts of data, including receipts for the purchases of millions of target people, helps marketers estimate the actual effect of an online marketing campaign. Suppose an online ad doesn’t lead to an offline purchase. In that case, a marketer is likely to waste the budget and, as a result, should change the ad (the platform, communication format, the message, the target audience, etc.).

7. Increasing customers’ loyalty

No wonder that major insurance companies prioritize customer retention. Attracting new clients may cost five times more expensive than keeping existing ones. Increasing customer loyalty requires data – the more, the better. By analysing sales, insurance companies understand what other products they can offer. For example, an insurance company has three similar products, and its customer has already bought two of them. The client will likely be sensitive to the third product’s advertisement.

8. Data visualization

90% of marketers rarely use data visualization in their work. However, visual data is more transparent for the viewer than pages of text. It allows marketers to convey the main points to the reader quickly. Data visualization helps analyse marketing campaign results and can be used by professionals in insurance marketing. It is more convenient for an online marketer to study sales dynamics when you have a graph in front of your eyes.

9. Calculating marketing budget and forecasting sales

Exploring customer buying patterns helps marketers anticipate future sales. To be more particular, the calculation of customer metrics (acquisition cost, average bill, customer lifetime value) allows an insurance company to understand how much revenue each new client will bring in the future. If a company doesn’t count these metrics, it is challenging to conduct practical marketing activities.

To sum up, big data today is an integral part of the advertising market, including the insurance business. Regardless of the tasks and distribution channels, big data analysis makes it possible first to develop an effective advertising campaign and then assess the benefits received from it.