September 10, 2019
Rolling out a comprehensive data integrations strategy for your SaaS company has many benefits. We’re listing 9 good reasons. Here we go…
Cloud applications are all about connections. Let’s look at marketing automation software. For a long time a discussion went on, whether companies should invest in one integrated suite that ‘does it all’, versus a best-of-breed approach where multiple niche tools are combined to build an overall marketing stack. The reality today is that you need both: companies need a comprehensive central marketing automation suite, and additionally specialized tools to take care of various aspects such as social media marketing, mobile marketing, retargeting etc.
It goes without saying that good integration capabilities are key in such an environment. Niche marketing tools need to offer integration capabilities, otherwise they become a data silo within the customer’s organization. Marketing automation suites on the other hand need to enable data integrations with niche tools, to allow customers to fulfil their needs.
It gets even more complicated as companies need to appoint a “single source of truth” for their marketing data: a single database that holds the master customer data. Is that the CRM or the marketing automation suite ? or is it a DMP (Data management platform) or even a CDP (Customer data platform) ? In any case, data integrations, and more specifically data synchronization capabilities are key in building and maintaining a “Single source of truth” (SSOT).
Big data is a main driver for integration capabilities. Big data is about aggregating all the data available within a company to improve decision making. Big data tools are used for Business Intelligence (BI), analytics, dashboards, data enrichment, user profiling and much more.
User profiling for example is a common practice in display advertising: a profile of an individual is built in order to apply personalisation on ads, and also for so called “programmatic buying” of display ads, using RTB (real-time bidding) to purchase individual ad impressions. Without going into details, note that data of multiple sources are combined to build the user profile, and the quality of the profile is essential in order to optimize the budget spent on display advertising.
Recently the word “Data democratization” was introduced in order to express the need to make data available to everyone in an organization. Let’s take for example user behaviour data, which is collected in various SaaS applications used within an eCommerce company. This data can be used by engineers to optimize certain processes. The same data might be useful for finance, marketing, sales and anyone else within the company that’s even a bit data-savvy.
That’s where tools such as Blendr.io come in handy: Blendr.io allows data to be collected from multiple SaaS tools through ready-to-use connectors. Next, the data can be exposed in a controlled way to both a technical audience within the company such as software engineers and developers, and a non-technical audience such as a marketing team. Everyone gets controlled, secure and easy access to the data they need, to improve the operations of their department.
Machine learning and artificial intelligence (AI) have made their introduction in each industry. Machine learning algorithms typically need to be “trained” on available company data. Once trained, the machine learning algorithm can make some sort of prediction, based on new incoming data. One example is predicting which website visitor is likely to buy, based on her behaviour on the website.
Data integrations play a key role here: data integration platforms such as Blendr.io, allow to easily connect the sources of data (e.g. eCommerce, website CMS, analytics tools) with specialized machine learning services such as Amazon AWS Machine Learning.
SaaS providers should consider expanding their data integration capabilities, and become part of strategic ecosystems. Ecosystems can be an important source for leads. One example would be niche SaaS players that become part of the ecosystem of Salesforce (the Salesforce AppExchange app store), the Marketo ecosystem (Marketo Launchpoint) or the Hubspot ecosystem.
Of course, there are many more ecosystems out there, for example within the IoT (internet of things) movement, and personal assistant ecosystems such as Amazon Alexa. By integrating with Amazon Alexa, your company offers a new “UI” to your users, which is voice controlled. But more importantly, you open up a potential inflow of new customers that discover your software through the Amazon Alexa ecosystem.
Enterprise-grade SaaS applications will typically respond to RFP’s (requests for proposal), to acquire new customers. A comprehensive RFP to purchase SaaS software, will most likely contain paragraphs or even chapters dedicated to data integration requirements. That’s because the purchasing enterprise wants to avoid creating data silo’s at any cost. This is a good example of how data integrations capabilities are more than just a technical matter. In order to respond adequately to RFP’s, companies need in-house knowledge to propose integration scenario’s, and they even need adequate knowledge on the software they have to integrate with.
Do you remember the expression “mobile first”? A couple of years ago SaaS companies needed to become “mobile first”, which means they had to optimize the user interface (UI) for mobile devices such as smartphones and tablets, without losing sight of a classic screen size of a computer.
Similarly, today the “integration first” paradigm is becoming equally important. In analogy with the previous paradigm, software applications have to be designed with data integrations in mind, right from the start. API’s are not just an add-on to an overall architecture, they are a fundamental corner-store of each SaaS application. Being an “integration first” company will allow you to be flexible and act quickly on new opportunities that will arise.
When your company is an “integration first” company, chances are you will be evolving to a micro-service architecture. In a micro-service architecture, smaller units of logic run as a stand-alone service, with a clear interface to other units of the overall application. In many cases the interface of a micro-service is an API. Micro-services have many benefits, especially since they keep the borderlines of various parts of the overall platform clear, and they allow to replace one unit without affecting other parts of the application.
In case you’re still not convinced of the need to put an integration strategy in place, let’s look at the numbers. The data integration market is booming! The iPaaS market (integration platforms as a service) is expected to reach $3 billion by 2021. The data integration market is expected to reach $12 billion by 2022, and the Enterprise application integration market is expected to reach $33 billion by 2022. Sources: Gartner, Aberdeen, Forrester.
Are you considering to publish an API or you want to replace your ad-hoc integration efforts with a comprehensive ecosystem? Download the full “The SaaS integration strategies Bluebook”.