Data was and continues to be a gold mine for many businesses around the globe. Countless product improvements and optimizations have been made based on the insights gathered from customer data.
Fast forward to the present day, many sales teams and investors continue to assume that customer data can give them a competitive edge forever. They also believe that the more customers they have, the more data they can gather, and that data, when analyzed with machine-learning tools, allows them to create a better product and drive profits. But this is not always true.
Most of us overestimate the advantage that data confers. Frankly speaking, massive volumes of customer data are not enough to be successful. Data-enabled learning is necessary and we’ll discuss it throughout the blog.
We’ll walk you through –
- Background of traditional data analysis models
- Data-Enabled Learning: How it provides a competitive advantage
- 3 important questions to answer when using data-enabled learning
Background of Traditional Data Analysis Models
Information aggregators like LexisNexis, Thomson Reuters, and Bloomberg have built their success on customer data. Gathering customer information and using it to improve products and services is an age-old strategy. The process is slow, limited in scope, and difficult to scale up. Traditional methods include crunching sales data, conducting customer surveys, and holding focus groups.
The time-consuming processes were gradually replaced by cloud and other innovations in business intelligence (such as Managed Analytics). This led to the concept of data-enabled learning.
Data-Enabled Learning: How it provides a Competitive Advantage?
Data-enabled learning algorithms in analytics solutions help firms to quickly process and make sense of vast amounts of data. They can directly collect information from CRM systems about customers, including their personal details, choices of content, search behavior, communications, GPS location, social media posts, and usage patterns. Machine Learning algorithms then analyze this data to reflect the findings, which are tailored to individuals. This is how the reports look in reality.
We can say that data-enabled learning is much more powerful than ordinary customer insights. They are not, however, foolproof when it comes to outsmarting your competitors.
You need to answer some important questions while using data-enabled learning.
3 Important Questions to Answer when using Data-Enabled Learning
1. How much value can the customer data add to the stand-alone value of the offering?
The answer to this question depends on whether your business model relies heavily on customer data.
For example, the value of customer data is very high in Advanced Driver-Assistance Systems (ADAS). It’s a matter of life and death for drivers relying on such systems. Car manufacturers have to test the system thoroughly before implementing them in the vehicles. This testing is done by collecting the test data and analyzing it. EZlytix has undertaken similar projects in the past for different industries and improved the data’s accuracy by up to 99.99%.
Conversely, the value of customer data is relatively low for manufacturers of smart televisions. Improving the recommendations of TV shows based on users’ viewing history doesn’t help much. Consumers don’t care about such features (offered by Amazon and Netflix). They are mostly interested in TV size, ease of use, picture quality, and durability when making buying decisions.
2. How quickly does the marginal value of Data-enabled Learning decrease?
This question simply means how soon a company reaches a point where additional customer data does not enhance the value of an offering. While answering this question, you should judge the marginal value based on the customers’ willingness to pay and not by some other application-specific metrics.
If you notice a higher marginal value even after acquiring a very large customer base, your products and services have significant competitive advantages. Google is a good example of this. Microsoft spent years and billions of dollars in Bing but could not shake Google’s dominance in search.
Smart thermostats are a counter example of a business where the marginal value of user data drops off in a short span of time. These products can learn users’ temperature preferences quickly. Hence, data-enabled learning can’t provide much of competitive advantage in this case.
EZlytix’s customized reports can deliver the required insights to understand what’s valuable and what’s not.
3. What are the issues faced when imitating product improvements based on Customer Data?
Even if you have data that is proprietary and produces valuable insights, it’s not easy to build a durable competitive advantage. Your product’s enhancements can be copied by competitors.
There are two ways companies can overcome this challenge.
A. The improvements should be hidden or deeply embedded in a complex production process, making them hard to replicate. Pandora is a music-streaming service that benefits from this barrier. It leverages the proprietary Music Genome Project, which categorizes millions of songs on the basis of some 450 attributes. This cannot be easily imitated by any rival because it is deeply related to the Music Genome Project.
B. If the customer data changes often, companies can protect their product improvements effectively.
The faster the data changes, the harder it becomes for others to imitate. For example, the Google Maps interface can be easily copied in many aspects. However, Google Maps’ real value is its ability to predict traffic and recommend optimal routes. This is not easy to copy as it leverages real-time user data that becomes obsolete within minutes.
Data-enabled learning is a broad topic and there are many more questions to be answered when using it. But we are limiting this article to only three of them.
Data, when used correctly, can work wonders for your business. You need to equip your team with the right analytics tools to scale your profits. EZlytix is a SaaS-based Managed Analytics solutions provider that can guarantee you an ROI of nearly 1200%. get in touch with our consultants to find out more.