The Value of Customer Data
Lots of people think that customer data and especially if you have a lot of it, is very valuable and can even provide a
(sustainable) competitive advantage.
And of course certain companies offering various software tools for collecting and/or analyzing customer data try to convince you of just that.
However customer data is not always valuable. And even if it is, there are conditions that determine to what extent that is the case, how long the value might last, and if the data might represent a competitive advantage or even a sustainable one. Hagiu and Wright describe 7 practical questions to assess these conditions:
1. How much value is added by customer data relative to the standalone value of the offering? The more, the better.
2. How quickly does the marginal value of data-enabled learning drop off? How quickly is the point reached where additional customer data is no longer valuable? The slower that is the case, the better.
3. How fast does the relevance of the user data depreciate?
4. Is the data proprietary - meaning it can't be purchased from other sources, easily copied, or reverse-engineered?
5. How hard is it to imitate product improvements that are based on customer data?
6. Does the data from one user help improve the product for the same user or for others? The former might make existing customers more sticky, the latter might help to attract new customers.
7. How fast can the insights from user data be incorporated into products?
I recommend reading this excellent no-nonsense article if you're interested to learn more about each question.
Source: Andrei Hagiu and Julian Wright, "When Data Creates Competitive Advantage", HBR Jan. 2020, pp. 94-101.
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Comments
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Chloe Xu
Director, Australia
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Regular and Data-Enabled Network Effects of Customer Data I agree regular and data-enabled network effects can be important for businesses to establish a strong competitive position. It is a common belief that more customers and the information we have, the better we can use the data to create a product that the customers want. However, we should not overestimate the (sustainable) competitive advantage which such data offers not the defensible barrier it may provide against competitors.
Just like regular network effects, data-enabled network effects CAN provide barriers to entry. However, they have key differences as below:
- Given buying data is easier than buying customers, the cold-start problem is less severe for the data-enabled ones.
- To produce sustainable data-enabled network effects, a business must keep learning from its customer data. Regular network effects allow interactions between customers to generate value automatically, even the product stops innovating.
- A firm can benefit from learning its user data at a relatively small customer base, and sometimes, it does not benefit further from any additional customer information. Regular network effects extend further and are more resilient, which means a single new customer still enhances value for existing customers, even the customer base is already huge.
The most successful businesses for the future will be those who build their regular network effects and are enhanced by data-enabled learning.
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