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Definition of Business Analytics Category

A business analytics platform serves the purposes of data preparation, intake, visualization, and insight discovery. A Business Intelligence (BI) platform’s modernity lies in its decreased reliance on IT teams to store information and define data models. What citizen integrators are to iPaaS, citizen data scientists are to business analytics.

Where does the demand for modern BI come from? According to a Harvard Business Review survey titled “An Inflection Point for the Data-driven Enterprise,” 86% of respondents report that the ability to extract new value and insights from existing data/analytics applications is “very important” for the data-driven enterprise, however, only 30% of respondents report that they are doing this effectively.

Predictions for the BI Market

Although researchers disagree on the exact amount, they agree that the BI market is growing. Stratistics MRC expects the business analytics market to reach $71.1 billion by 2022, growing at a CAGR of 6.9% from 2015 to 2022. According to AppsRunTheWorld.com however, the analytics and BI applications market will reach $14.5 billion by 2022, compared with $12.3 billion in 2017 at a compound annual growth rate of 3.3%.

Regardless of the exact rate, BI market growth faces stalls in the form of high execution costs and users’ unwillingness to adopt BI solutions that fall short of their expectations for ease of use. The key to ensuring higher adoption and therefore higher ROI lies in giving users what they demand. On BI vendor Sigma’s website, research firm Gartner predicts that “by 2020, organizations that offer users access to a curated catalog of internal and external data will derive twice as much business value from analytics investment as those that do not.”

Leading Vendors in Business Analytics

As shown on AppsRunTheWorld.com, here are the leading BI platform vendors by market share. In 2017, SAS institute had 14.5%, followed by SAP, then IBM, then Microsoft, then Tableau.

So why don’t Gartner’s BI market leaders such as Microsoft, Tableau, and Qlik enjoy the highest overall market share? Do they have better timing, marketing or cross-selling operations? What are each of these vendors doing to protect their claim or gain ground from their competitors?

iPaaS: A novel way for BI to differentiate

According to Stephanie L. Woerner, a research scientist at the MIT Sloan Center for Information Systems Research (CISR) and coauthor of “What’s Your Business Model? Six Questions to Help You Build the Next-Generation Enterprise,”

“It’s hard to do really good analytics when data is all over the organization and its systems. Integrating silos is a core capability. It doesn’t mean you can’t start transforming without integrating data, but it makes it much more difficult, and there’s a real chance of actually making things worse for the customer.”

The following paragraphs elaborate upon why eliminating data silos and providing business intelligence increasingly go hand and hand.

BI Platforms will embrace iPaaS

TIBCO, the vendor in position #7 of Gartner’s BI Magic Quadrant, in June of 2018 acquired iPaaS company Scribe, which allows businesses to easily connect to their applications. Expanding connectivity capabilities to a broader set of applications accelerated TIBCO’s entry into new market segments. Furthermore, having Scribe in-house allows TIBCO users to benefit from connectivity as well as business intelligence capabilities all from within a single platform.

Similarly according to integration provider Dell Boomi, “if business users can’t pull data from various sources, there’s no useful data analysis and no BI. More specifically, if the data has to be pulled from each application, there’s a high risk that the data is inconsistent or inaccurate.” Hence the inseparability of integration and BI capabilities.

iPaaS will hug BI back

iPaaS vendor Mulesoft stated in their report that, “trying to extract actionable insights out of data housed in a static data warehouse will ultimately be doomed because it is impossible to meet everyone’s business needs with a single system.” The report goes on to explain, “because there are multiple sources of data that feed into business intelligence systems, there needs to be a way to unite them.”

Which integrations do BI platforms need most?

According to Dresner’s 2019 study “Wisdom of Crowds Business Intelligence Market Study,” the majority of respondents cited “growth in revenues” as very important or critical to their BI objectives. Without BI platforms, companies generally view their revenue in their CRM of choice. So it’s no surprise that new BI platform users’ first step is often called “Connect your data,” followed by instructions for hooking the BI platform up to Salesforce.

Integrating BI solutions with users’ CRMs provides users with the shortest time to value, which increases adoption and consequently their lifetime customer value (LCV). However, despite Salesforce’s dominance in the CRM market, they do not serve such a majority of users that BI platforms can rest on their laurels after integrating with Salesforce alone.

According to IDC, Salesforce continues to lead the CRM application market. See the chart below, which is publicly available from Salesforce here.

As you can see above, combining the market share of the next four top vendors on the list amounts to a greater market share percentage than Salesforce’s entire share. Given that so many of their prospects prefer one of the secondary vendors (and more likely need to access a variety of them within their large enterprise), users of the non-Salesforce products comprise too many potential BI platform users for BI companies to leave on the table. So how are BI companies meeting this growing expectation of prospects that their BI platform serve up built-in connectivity with their CRMs of choice?

Key BI companies fall short of supplying the native integrations their customers demand.

The chart below shows the top 14 BI vendors in the left column. It then shows six market-dominating CRMs horizontally across the top. The red and green cells indicate whether each business intelligence vendor provides their users with native integration to that CRM.

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“In house” indicates that when contacted, representatives from that vendor confirmed they have a native integration to that CRM. “No/external” indicates that the connectivity was built by an external company or requires an external partner to implement. For some of the vendors, the nature or presence of an integration is unclear or unknown (and we’ll continue to update this chart as/if we hear differently).

The cost of not prioritizing integration

According to Dresner Advisory Services’ Wisdom of Crowds Business Intelligence Market Study, “User feedback is the preferred measure of success; lack of usage is the preferred measure of failure.” And, “Net BI product replacement is 27 percent in 2019, most often for reasons of functionality.”

The downside of failing to provide native connectivity can be felt in the short and the long term. At the outset, increasingly savvy line of business leaders will back away from deals that promise a nightmare integration process. The complexities of exporting CRM data to an outside warehouse and importing into the BI environment will make their heads spin. Perhaps the more delayed downside appears in the resistance to adoption by those users who discover that their new BI tool does not play nicely with their CRM of choice. Un-adopted products pave the way for replacement vendors who are willing to provide connectivity with all the popular and even the long-tail CRMs out of the box.

Best practices for CRM API integration with BI


Integrating your BI application with multiple CRMs sounds like a great plan until your engineering team realizes how much work it is to connect your product to HubSpot using their API, not to mention starting over to then integrate SugarCRM from scratch. This is when outside tools such as Kloudless can help.

Product teams use Kloudless’ Unified CRM API to connect their business analytics product to multiple CRMs with a single implementation.

So if you’re Tableau, you can quickly provide not just two, but a long tail of CRM integrations for your users.

Implementation of CRM integrations

It’s not enough to have integrations; the integrations themselves must be easy to implement. For example, although some BI platforms boast hundreds of externally-sourced integrations to other apps, reference customers cite difficulty in implementing the connections. What’s worse, BI platforms often tell prospects they can integrate with anything when what they really mean is that the prospect must export to a data warehouse and re-import to get the connectivity. Naturally, their users would prefer a stronger, native integration with external CRM tools. Product teams that leverage Kloudless Unified APIs don’t need to worry about murky implementations. They connect to the Kloudless API and let Kloudless worry about version maintenance and the troubling quirks of each underlying CRM’s API.

Embedding CRM connectivity within SaaS products

In Salesforce’s State of Analytics survey, the majority of respondents said their top concern with regard to BI solutions was “getting all the necessary data into one view.” The best way for Salesforce (and any vendor) to achieve this is via embedded integrations.

Here’s how analyst firm Gartner explains this need on Prologika’s website: “These capabilities can reside outside the application (reusing the analytic infrastructure), but must be easily and seamlessly accessible from inside the application without forcing users to switch between systems. The capabilities for integrating BI and analytics with the application architecture will enable users to choose where in the business process the analytics should be embedded.”

In other words, one of the surest ways to lose a customer is to require that they exit your product environment in order to complete a common task. Non-native integrations between business intelligence systems and CRMs do just that. They require that the user sign in to another service provider to access the CRM functionalities they need. On the other hand, when BI companies build integrations directly into their product, their users access CRM functionality without ever leaving the product environment, thereby enjoying a better experience and reinforcing trust in the BI product’s brand.

The BI platform connectivity checklist

How does your business analytics platform measure up? Do you support workflows from data to self-service analytics to systems of record? Are your self-service workflows user-centric, including on-demand interactivity? Can your users connect easily to data and actions in their CRMs of choice? And when they do this, are you keeping them within your product environment or forcing them to authenticate with a third party service? Last but not least, are you creating more technical debt with your SaaS integration strategy or are you simplifying? How much time and energy is your engineering team spending on API version maintenance and one-off SaaS integrations rather than on improving your BI product?

If the answers to any of these questions are no, Kloudless can help. Get in touch with an expert here to have a discussion about how to streamline your BI platform’s SaaS integration strategy.


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