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Why businesses should buy, not build, embedded analytics

Scott Castle is VP & GM of products at Sisense.

It’s now widely acknowledged that being a data-driven organization is vital in today’s fast-moving, ever-changing business environment. Using analytics to hone your efficiency, performance, services, and products is no longer a luxury. It’s a “must-have.” That’s why 92% of executives say they are continuing to increase investment toward being a data-driven organization, according to a survey by strategic advisors NewVantage. Executives know that analytics are important because when they use data, their businesses perform better. With this in mind, the big question for businesses is no longer “should we get analytics?”— it’s “should we buy it, or build it?”

Embedding analytics is the new ingredient for success

Analytics gives companies a competitive edge in terms of profitability, audience engagement, and customer retention. McKinsey Global Institute says that companies are 23 times more likely to get new customers, six times more likely to retain existing customers, and 19 times more likely to be profitable when they use insights derived from data and analytics.

The impact is particularly powerful when embedding analytics in your product or application. Apps that use data-informed messaging for audience engagement saw a 25% improvement in retention. It’s no surprise, then, that in just a year, the number of product teams planning to use analytics this year has reached 40%, up from 27% in 2020, according to an IDC survey, commissioned by Sisense.

Build a solution? Better not

You might consider building and embedding your own analytics solution, because you may think that doing it yourself could be more cost-effective. Perhaps you’re unsure of your market’s needs. You’re not sure whether your customers need sophisticated analytics or just basic reporting, and you don’t want to overinvest if you don’t have to. Tasking a couple of developers to build a simple solution in a few sprints seems like an inexpensive approach compared to buying a commercial solution. Plus, you won’t need to build a business case or justify the decision. Perhaps you’re keen to empower your engineering team to build an analytics prototype, because it seems like a quick solution, and you don’t want to discourage them. So, building just a little at a time seems more prudent. In all of these scenarios, the return on your investment might seem quicker and easier to attain, but only if your needs are limited, and you don’t encounter challenges in implementation or scaling up. As we’ll see, this is often a false economy.

Another consideration is creating a seamless user experience. By building analytics in-house, you might feel that you have complete control over the look and feel of your analytics to be sure it matches the appearance and user experience of your existing products and services.  Understandably, you might want to avoid sacrificing design freedom to a third-party vendor. You’d like users to identify the embedded capability as your own and acknowledge that it’s your business adding value to their experience.  But the best modern analytics platforms address this need with white-labeled analytics. They’re built for embedding and for customizing their product for companies’ specific needs. And they’re created by experts in the field to provide you with the best results.

The best way to get it: Buy it

Even with all of these considerations in mind, buying is ultimately the smarter choice. And there are other compelling reasons for buying your embedded analytics rather than building it yourself.

First is speed. A specialized, dedicated analytics vendor is your quickest path to implementation and offers the shortest time to market. That’s because they’re the experts. They’ve overcome every challenge and obstacle to implementation. A good analytics provider can assure delivery on time and within budget. Can you be so sure that your in-house team can do the same? It’s a cliché to say that time is money, but it’s true. Buying may require a larger initial outlay, but if it means ramping up faster and more comprehensively, then it’s worth it.

Second is the user experience. Your vendor of choice should be able to tailor an analytics solution to your particular needs. The best providers deliver functionality that looks and performs just how you want it to. They don’t provide an off-the-shelf solution because they know that these days, one size fits nobody. Customization is key, and it’s important that a vendor can match your branding, color scheme, fonts, look and feel and any other UI features.

Third is scalability. Without a doubt, your aspirations for your business are growth: more business, more customers, more products and more service lines and features. That generates more data in more formats from more sources, and it means you’ll have many more users. Building a solution yourself typically enables companies to handle their current data needs, but rarely does it provide the flexibility and agility to scale up as your business grows. Growth seldom runs smoothly, and you need to be assured that you have the analytics you need, precisely when and how you need it, to glean the best benefits for your business.

For instance, can you be sure that your product rollouts will go as planned? Could a spike in users, subscribers, complex features and so forth, put your architecture under strain? Can your analytics platform handle new types of data that you’ll generate, in much larger volumes, irrespective of its type? Are you tied to an on-premises solution, or one particular cloud services provider? Or do you have the flexibility to work in any cloud and in a hybrid fashion with your cached data on-premises? It’s unlikely that jumbling together an in-house solution means you can confidently and positively answer all these questions. Buying in a dedicated provider gives you the assurance that you can.

Future-proof and constantly innovate

The thing about change is that you can’t always predict how progress will happen. So, you need to be able to innovate your analytics, to keep it relevant and effective not just for your current needs, but also for future growth. This means you need access to the resources, the ability, and the know-how to address such progress. Innovation and future-proofing are the fourth and perhaps biggest consideration.

Have you got enough team depth to deliver what you need? Can they build and maintain new capabilities and features? Can their home-grown solution handle and maintain the few million more lines of code and the escalating volume and variety of data that come with growth? When you build from scratch, this is all on you. It requires a lot of labor, resources, and expertise. When you buy your analytics and infuse it into your product, service, or experience, you can get better analytics, faster, with less work in the long run.

Work in partnership to get the best for your business

Leveraging a long-term partnership with an analytics provider means you have the support of a team of experts dedicated to innovating their offering so you can evolve yours. This frees your development team to stay focused on your core product, while your analytics provider will periodically roll out new functionality that will enhance your offering. With a provider’s support, you’ll seamlessly embed analytics into your product or service that matches your house look and feel. You’ll deliver better features faster, with fewer maintenance concerns, and you’ll enjoy the benefits of ongoing innovation. If you want to work smarter, not harder, buy your analytics instead of building. It’s best for your business now, and it’s the way to go to assure success in the future.

Scott Castle’s Bio:

Scott Castle is the VP & GM of Products at Sisense. He brings over 25 years of experience in software development and product management at leading technology companies including Adobe, Electric Cloud, and FileNet. Scott is a prolific writer and speaker on all things data, appearing at events like the Gartner Enterprise Data Conference, Data Champions, and Strata Data NYC.