In the third installment of our Embedded Analytics Series with Tableau, we break down a discussion on the classic Build vs. Buy scenario from the perspective of data. Featuring a diverse panel of thought leaders and solutions engineers, including the former Head of Precision Marketing at powerhouse Carrefour, the panel discusses the merits of building an internal data analytics solution versus the investment in an external solution that brings a competitive to the product.

Before we dive in, put aside a few minutes to catch up on how Data Monetisation with ICIS and Turning Data Into Products with Experian. We’ll conclude the Embedded Analytics Series with Accelerating Insights with Grindrod, a conversation on how embedded analytics bolsters data-driven decision-making by allowing users to access reports and visual displays directly within an application user interface.

The value of interactive data visualisation

“Sharing data and insights to external audiences is not necessarily a new phenomenon – organizations have been doing it for quite some time. A lot of this has been done in the form of raw data, insights, or static reports.”

As stated by Mrunal Shridhar, Tableau Sr. Manager of Solutions Engineering, the value of raw data is becoming more apparent to product leaders with each new quarter. The challenge lies in the visualisation of that raw data, a problem Tableau provides multiple solutions to. Timo Tautenhahn, Tableau Principal Solutions Engineer, begins the discussion with an in-depth demonstration of the flexibility of the Tableau dashboard in visualising different data segments. 

“There are many companies out there who are selling raw data, insights, or static reports. The ability to take that data and turn it into an interactive, visual representation that allows users to drill deeper into the various product categories of their customers, makes that data even more powerful with higher value. That’s why interactive analytics is so important to today’s embedded analytics cases.”

Build Vs. Buy Considerations When Using Embedded Analytics

It’s a question that product leaders face at every step of the product lifecycle, especially if the organization is about to incorporate an embedded data analytics approach into its digital transformation strategy and customer products. When is the time to build a feature internally, and when is it wiser to simply buy and integrate?

Fortunately, data is the key to making that decision and to receiving a competitive advantage. Getting into the meat of the discussion, Timo first lays out the points product leaders need to consider when approaching a build vs. buy scenario.

“There are a few things to consider, the first one being speed, or the time to market, and the second one being skills. Some companies think being a developer company means building something of their own, but there are a lot who are not coding their own solution because they’d rather focus on developing their platform rather than creating reports, which you can do with self-service API solutions like Tableau.”

While skill and speed to market are important considerations, John Greca, the Fmr. Head of Precision Marketing at Carrefour, draws from over 15 years of experience in online sales and personalization to express that “the power of Tableau really comes down to scalability and operating leverage”. He continues on by expanding on why data is that key component to scaling a product after go-to-market.

“When an idea goes to market you hope for the best, meaning you have more clients, more customers, and more revenue, but what people don’t consider is the cost associated with operating the business. Usually, this cost follows the same trend as the revenue. A solution like Tableau lets you see the variable costs, and by reusing components, or standardizing capabilities for other clients that have the same question, you can make it available at scale.”

“This will have a growing effect on the margin, especially the ability to time your cost. By definition, your monetization strategy is going to increase your operating leverage and the associated margins.”

Business cases around using Embedded Analytics

John Greca puts it succinctly when he says “with any kind of idea you need to go fast and prototype that idea”. Sometimes buying externally is exactly what’s needed to achieve an experience-driven proposition as fast as possible. John rounds out his remarks by sharing why Tableau was the best choice for Carrefour when considering an alternative to building internally.

“We had to come up with a compelling business case around the assets and how we could monetise these assets to our partner. At the end of the day, with Tableau, we have the data and the ability to visualise that data in a powerful way that is scalable. We wanted to rapidly evaluate the ROI of our ideas, and buying a solution from Tableau was the best alternative to building that functionality.”

Once a feature has smoothly gone to market, the next goal is that ever-elusive “stickiness”. Geoffrey Smoleers, Founder of Biztory, one of the foremost Tableau partners in EMEA, dives in to share why now is the time for companies to employ an embedded analytics solution.

“If you want to expand your business from a revenue point of view, get new revenue streams, and also increase your stickiness with your clients, I think those are the most important reasons to start creating a better analytics solution. Customer service is more important now than ever and with the power of social media, companies can be reviewed and killed within minutes or days, so companies need to do everything they can to increase stickiness.”

The need to monetise data often plays a big role in the decision to roll out external analytics or embedded analytics project, says Mrunal. Product leaders have to approach the decision to build vs. buy with care, precision, and ultimately, with the data to back up that decision.

“The build vs. buy decision can dictate the success or failure of your project. Going with an industry-leading solution like Tableau allows you to focus on what is important; your customers, your stakeholders, and most importantly, your business, rather than spending time, energy, and money on building your own solution in a space that is not necessarily your core expertise or interest.


We’ll conclude our Embedded Analytics Series with a final panel on Accelerated Insights at Grindrod. If you’re currently considering embedded data for your own company, we’d love to hear your thoughts on the ways you use data during your own product development. Feel free to comment below and let us know what you think about the embedded analytics solutions available to product leaders.