Data acquisition: With three rules to trustworthiness
The data of customers and prospects is valuable for companies. But many consumers are, quite rightly, cautious and use their data sparingly. They look very closely and share only as much information in transactions as is absolutely necessary. Companies should therefore invest in their trustworthiness. A high level of data security and transparent handling of data in accordance with data protection and information security specifications and guidelines are important aspects in this regard. This applies particularly to financial and insurance services. Here in particular, the request for too much and, above all, irrelevant data tends to have a deterrent effect before the digital conclusion of a contract.
Data retrieval is an important moment for both sides. On the one hand, insurers want to obtain as much data as possible about their customers so that they can, for example, use it as a basis for personalizing marketing measures or developing needs-based additional offers. On the other hand, potential customers want to disclose as little information about themselves as possible. For many consumers, an inappropriately extensive data query is therefore already reason enough to cancel the contract.
Now an EOS study from 2020 also says: Consumers are generally skeptical of companies that process their digital data. The level of distrust also depends on the industry. After all, 54 percent of respondents in Europe trust banks to handle personal data responsibly - which puts them in the best position compared to other industries. Even the most trustworthy institutions are relied on by just over half. In the case of insurance companies, the figure is just around one-third. Not a good basis for promoting further data donations.
Engaging customers through user-friendliness
Anyone offering digital financial or insurance products needs process know-how and a professional approach to data. It doesn't matter whether you're a startup or an established institution. Knowing your customers and their needs is essential. A transparent customer journey without media discontinuities is definitely the top priority. Errors, complexity and disruptions, especially during registration and contract conclusion, can be expensive.
On the one hand, interested parties and potential customers on the digital path to concluding a contract expect products to be presented and explained clearly and comprehensibly. On the other hand, user guidance, especially in the form input, has a major influence on whether or not the contract is concluded. Insurers and financial service providers are now faced with a dilemma: if they ask for significantly more data than is required to conclude a contract, this not only scares away potential customers, but also conflicts with the principle of data economy. According to this principle, only the data that is required for the respective purpose may be collected and processed. In addition, they are subject to strict regulations, for example for compliance risk management.
For the companies themselves, clean handling of data has further advantages: Unnecessarily large volumes of data lead to higher costs simply due to data storage. Data management also benefits from a reduced volume of data - for example, through lower energy consumption.
The most important rules for forms
So what should financial and insurance service providers pay attention to in the "last mile" of digital contract conclusion? At which point are interested persons willing to enter which data? Where are default settings or selection options helpful? Which data query has a deterrent effect and where must the protection of sensitive data be particularly emphasized?
Customers expect the entire process around information and contract conclusion to function seamlessly. This includes, among other things, a visit to the website to find out about the offers, the conclusion of the contract itself, and then customer service support. To ensure a smooth process here, providers must collect certain data. The question, however, is at what point in the customer journey this makes the most sense. For example, it is very tempting for insurance companies to require a customer account for the configuration of rates. That way, they would already have name, address, e-mail, and other relevant data at hand - for example, the vehicle model for a car insurance policy or the size and location of the apartment for a home insurance policy. However, data protection also always requires the possibility of so-called guest orders, i.e. without registration with a customer account. If customers have to submit their data before they can obtain information, they are very likely to abandon the process and look around at the competition or where the interaction costs are lower in terms of the individual customer objective. It therefore makes sense to offer a customer account as a selection option only after the fact.
The less effort it takes for customers and prospects, the better. This means: The input mask should be designed as simply as possible so that they can enter their data quickly, easily and in a structured manner with just a few clicks and entries. The mandatory fields should be clearly identifiable to avoid discontent. If, for example, it only becomes obvious after a form has been submitted that a field needs to be filled in, this leads to frustration and possible abandonment. Also, every data field that is not absolutely necessary increases the risk that prospects will leave the website. In addition, more fields also increase the likelihood of incorrect entries. Therefore, providers should make the input process as simple and short as possible.
Once customers have entered their personal data and other relevant information, it should remain stored for further processing. On the one hand, this avoids duplication of effort for customers, and on the other, it reduces the risk of incorrect data. If the data does not match, duplicates can occur, i.e. double entries. So if prospective customers are researching more than just one insurance product or financial service, they should only have to enter their data once.
More customer friendliness through tools
Intelligent data quality tools facilitate clean data entry. On the one hand, their use simplifies entry for potential customers and thus increases user-friendliness - on the other hand, they reduce errors arising from manual entries and thus improve data quality. Helpful functions here are, in particular, auto-completion and address validation.
The former opens a drop-down menu of suggestions as soon as prospects type the first letter in a field. The more information users type in, the more accurate the suggestions become. This significantly speeds up data entry - especially when using mobile devices. Single-line input, for example, is particularly helpful here - that is, entering the entire address in one line. In this way, the data is available in the system in a uniform and standardized form. The susceptibility to errors, for example due to mistyping, is minimized.
Address validation uses country-specific knowledge bases to check whether data entered is correct - and corrects it if necessary.
If an insurance company or bank also operates beyond Germany, it faces another challenge. Other countries have different address formats that can inevitably only be captured inadequately with the German standard format. While German addresses are structured field by field, French addresses, for example, are structured line by line. Also, the house number is placed before the street name. The position of the postal code also differs from country to country. Therefore, providers must offer the address fields for each country in the form used there in order to obtain correct data.
Insurers and financial service providers must be able to rely on a well-maintained database for their business. For various reasons, this is not at all easy - relocations, weddings, incorporations and, for example, street renamings make it difficult to keep a clean database. Therefore, they should always treat the data as a particularly valuable asset and use data cleansing to maintain it continuously rather than just once.
This also helps customers and prospects: they can be sure that providers only collect the data they need from them. This is how they build trust - a currency at least as important as data. After all, the best insurance offer or financial product is of little use if prospects are scared away along the way by poor user guidance or seemingly unprovoked data greed.
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