Cloud Pinup: Analyzing Data With DataRPM

Analyzing Data With DataRPM

The transformative power of cognitive data products in the struggle to retain customers

In a world where consumers expect more and more from the products that they buy and the services that they use, the intelligent and effective use of cognitive data services can make all the difference in the high stakes game of customer retention.

One of the most disruptive elements of high-growth companies like Uber, Netflix or Amazon is the way that they seem to improve their understanding of their customers over time. Netflix gets progressively more accurate at recommending content that you like as they receive more data about your viewing habits, while Amazon seems to understand the kind of consumer you are and how best to serve you efficiently. These amazing organizations are mastering the use of big data and machine learning and creating a business environment that other organizations are continuously trying to emulate.


Data scientists are key players in this new economy, and there is a huge demand for their services right now. It’s a highly skilled and complex field, and a widely cited report from the McKinsey Global Institute, the United States will experience a shortage of over 180 000 data scientists by 2018.


As a result of this shortage of data scientists, companies are increasingly turning to partners like DataRPM who are able to deploy cognitive data products at lightning speed to solve the specific business problems of recommendations and personalization and delivering actionable insights for the client to implement.


There’s an old adage which states that bringing in new customers is hard but losing them is easy. The phenomenon of customer churn refers to the loss of a customer or consumer to an organization and is a universal problem for companies big and small. For example, analysts estimate that US credit card companies deal with an annual churn rate of over 20% and considerable resources are dedicated to trying to reduce that customer leakage.

Of course, companies that spend most of their energy constantly trying to bring in new customers are rarely able to grow to the extent that they fulfill their potential.


Why is customer retention so difficult? Online, most customers are young, brand conscious and price sensitive. Fluctuating prices for subscriptions, multiple passwords to remember, complex barriers to entry and shifting tastes can all lead to high customer churn. Of course, the process of attrition is only worsened when a product simply doesn’t operate properly. Recently a leading telecommunication provider in France recently faced a major crisis.


(Image Source: Shutterstock)

They had a customer base of 10 million customers who were using their ITV set-top boxes, but nearly 42% of their boxes were throwing out errors and customers were deserting them in droves. The clients’ internal data team was able to identify 30% of set-top boxes that were likely to throw errors but that wasn’t getting to the heart of the problem. When DataRPM was engaged to work on the problem, the company deployed a machine-first approach with its Cognitive Data Product customized for the client’s issue and which automated the whole process of predictive model building. This allowed them to test all 50 000 set-top box models and select the one with the best prediction accuracy.

Inside eight weeks, DataRPM built a reusable model that not only predicted the types of errors that could occur, but also the 77% of set-top boxes which were throwing out errors and the reasons behind them. Ultimately, they were able to cut the clients’ operation costs by between US$3 – 5 million (through customer service), and help them retain 36% of their customer base, leading to an increased customer lifetime value of US$6.6 million.


The addition of cognitive capabilities to machine learning is transforming the arena of data science and leading to massive leaps forward in customer retention. The ability to let the machine figure out the best algorithms according to the data, as opposed to waiting for a data scientist to run different models, dramatically changes the scale and speed of the solution.

It’s a staggering breakthrough that effectively eliminates the problems caused by the scarcity of data scientists and allows companies to scale as and how they see fit. And the more data they process, the better their insights and recommendations become, leading to a virtuous cycle for clients and consumers alike.

Cognitive data products which positively impact customer retention, such as those offered by DataRPM allow clients to focus on their core products and delegate resources appropriately. For many companies, it’s a complete paradigm shift that helps them rediscover the reasons why they went into business in the first place.

By Jeremy Daniel

Jeremy Daniel

Jeremy Daniel is an author, online marketing strategist and a firm believer in the transformative power of mobile technology for emerging markets. Jeremy has written across various media platforms since 2001, from television to advertising to print, and spends most of his time in the beautiful city of Cape Town, South Africa.

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