Data valorization: Shifting to an alternative business model
All companies have been stating loud and clear “data valorization” as part of their strategic plan. No matter the sector (energy, transportation, banking, insurance …), data valorization is the new motto for all. Better valuing data has become a priority. By neglecting it, companies take the risk to lose a competitive advantage in the digital era we are living in.
Valuing its data in the context of a new digital ecosystem
Valuing its data is above all the ability to extract from it the answers to your company’s business stakes. In more detail, speaking about data valorization arises four major development levers to optimize the company’s activity or extend its business model:
- Operational performance: how to optimize my internal processes thanks to a better knowledge of the time devoted to each one of my activities, considering the new capacity to digitalize or in other words to automatize processes fully or partially …
- Personalization of the customer relationship: how to detect weak signals or determine the populations for which it is necessary to make customer advisors more available.
- Development of new services: how to adapt my offer and services. Thanks to a better knowledge of the penetration rate, it is easier to offer services that are more in line with customer demand (equipment, background, consumption, etc. …).
- Monetization of information: how to develop my business model in order to offer services based on the client held by the company.
Better value its data can be translated by the valorization of its own history of information, but this wouldn’t be enough. In the digital era, it is necessary to predict the competitiveness of new actors by adjusting quickly to this new ecosystem.
Especially in the banking field, personal data is the new Eldorado. In fact, differentiating the actors of the sector (or their newest competitors) won’t be simply based on the data linking the client to its bank but rather on the ability to gather and use personal data.
The competitive advantage can be even more considerable as banks would be able to capture “exogenous” events or in other words events occurring outside the client-bank relationship.
Moving from a service supplier to a data supplier:
In this context, a particular attention should be paid to the following points:
1- Determine the positioning of data in the value chain
In fact, there are different types of data:
- First party data: data collected directly by a company from its assets.
- Second party data: data collected by a company’s partner (the partner’s first party data) as part of a commercial action linking the two.
- Third party data: anonymous third party data. Today, it is a market held by specialized actors such as Weborama and Datalogix, but companies owning clients data can position themselves in the future in a similar way.
2- Don’t break off the virtuous circle with the client
In fact, the more data provided by clients enable to ease the consumption of an offer or a service, the more the level of trust of a client increases and the more willing he would be to provide personal information. This trust relationship should not be broken in any case. The acquisition of data should be part of this relationship.
3- Give a necessary consideration to the associated legal and security constraints in particular in terms of housing and management of optins/optouts.
Processing data in advance
From a methodological point of view, this repositioning obviously requires to process data in advance in order to:
1- Know and master your data to make them more exploitable
Establishing a global picture is necessary to have a complete and qualified vision of data sources for which quality should be measured.
Creating a common model of client data aims at sharing within the company a common representation of the client and the relevant data. One should be careful not to omit the associated notion of the lifecycle. Prospect, active client, inactive client, archived client, deleted client … the vision should be shared between the different entities of the company.
2- Enrich your data to make it more pertinent
Different ways are possible to enrich data. Improving the quality of intrinsic data makes it more pertinent. Adding other internal data completes the vision of the client (i.e. cost estimate, client complaint, contact …). Finally, an external enrichment increases the coverage of the available data.
Obviously, these improvements should respect the con-competition clauses and the commercial agreements that regulate the relationship between any company and its partners.
3- Make your data more accessible
The valorization of data as a data supplier requires making it accessible. Depending on the desired positioning, this can be done by anonymizing data, exposing the available data …
Data supplier … an economic model to reinvent
The company’s vision: choosing to make your clients data available tomorrow requires raising some crucial questions regarding your competitors. How do I keep my competitive advantage and monetize part of my data at the same time?
The client’s vision: Am I ready to allow the collection and distribution of my data with a larger perspective than just the completion of the service to which I subscribed in exchange of a financial compensation?
B2C, B2B, B2B2C… these models already exist, but what if in the future, a B2C2B model emerges where clients accept to make their data available to a larger community and get remunerated for it?