The News
On Monday, August 24th, 2020 SugarCRM announced the acquisition of node.io. I had the pleasure to get pre-briefed by Craig Charlton, CEO SugarCRM and Rich Green, Chief Product Officer and CTO SugarCRM about this topic.
Node was founded in 2014 with significant expertise, including ex-Google personnel and he creator of the Alta-Vista search engine. According to Crunchbase, the company has acquired $43.5M US to innovate around AI as a service. The company applies deep learning to help organizations make better predictions and decisions that impact their bottom line and focuses on delivering accurate predictions even with minimum CRM data. It does this by taking advantage of large data sets that it acquired or has free access to, including company and available business related personal information.
That way, it is possible to hand over only a limited amount of SugarCRM data to Node in order to achieve accurate predictions. Instead, the prediction engine runs almost exclusively on Node data. According to Charlton and Green, SugarCRM itself also does not see any personally identifiable data (PII) but only meta data out of the Node system.
One core idea behind the acquisition is that superior business outcomes need a combination of internal and external data. As Paul Greenberg gets quoted in the press release “now more than ever it is critical to leverage all available data and signals to work towards better outcomes for both customers and the business alike”.
SugarCRM compares the result of combining CRM data with the data and intelligence provided by Node to the switch from a low fidelity to a high definition view on the own business and its customers. The outcome of this switch is predictability, which in turn leads to the benefits of more revenue, lower cost, and reduced churn.
There is a clear go-to-market strategy. In the first three months after this acquisition SugarCRM will concentrate on driving awareness in the market and gaining deeper insights for productization. Then, in the next three months, the company will embed predictive, AI powered insights into the core product, based upon the existing value proposition. From then on, premium editions will follow.
In future, the Node system will exclusively serve SugarCRM customers.
The Bigger Picture
The capability to infuse data and AI into business applications have become table stakes for CRM and CX vendors. The value of CRM and CX systems is a result of their ability to provide insight, help people focus on the right customers and activities, and to make accurate predictions about the future and suggestions of what to do next.
All tier one vendors and a number of smaller vendors have built their own AI systems to accommodate for this. SugarCRM, in the process of getting its mojo back, needed to first concentrate on its platform to lay the foundation for building AI capabilities. The second step towards infusing AI capabilities into the business application stack is to make it easy to use. Most companies, certainly not those in the SMB market, do not have data scientists nor the resources to hire any. Instead they need systems with the ability to ingest data, train itself based upon this data and validate the training success, so that they can be used directly and without IT support.
In other words: The AI needs to work out-of-the-box.
Having a working AI is only one part of the picture. The other part is the availability of lots of data – and I mean LOTS of data – of different sources that help creating the models that allow the pattern matching necessary to generate accurate predictions. Primary sources for this data are the own transactional and associated systems, including voice of customer, DMP’s or profile building systems and server logs. Additional data comes via partnerships with data aggregators or search engines. This data covers anything from industry, company, people, market or any other public data, e.g. weather data.
My Analysis and PoV
In the 2020 Magic Quadrant for Sales Force Automation, Gartner noted artificial intelligence, “advanced AI-based sales technology abilities” as “modest in scope” when compared to the leaders of the quadrant. Gartner exemplifies “AI-based prescriptive next best actions and predictive engagement scenarios” as missing. While Gartner is not that candid on AI in the 2020 CRM Lead Management Quadrant it still refers to lead analytics as being one of the main cautions.
Consequently, SugarCRM was working on an AI strategy. Going the acquisition road certainly is targeted at increasing its implementation speed.
Before proceeding with the acquisition SugarCRM conducted some tests on its own data set with node and found that node significantly outmatched SugarCRMs predictions for the conversion of marketing qualified leads to sales qualified leads and from there to the conversion to closed won. Similarly, the tool achieved a remarkable accuracy of 88 per cent for churn prediction. In Craig’s and Rich’s words the accuracy of node on SugarCRM data “is as close to having a crystal ball as anyone …”
This test took all of 24 hours, which is testament to the simple API that Node offers, and quite remarkable, too.
I have rarely heard executives being that excited about acquiring a technology as Craig and Chris were during our conversation.
Given these figures and the ambitious roadmap, covering marketing, sales, and service, Sugar’s AI capabilities will certainly be delivered faster than originally planned.
The SugarCRM story of combining internal with external data sounds very similar to the SAP story of combining transactional and experience data. The main difference is in the second data set. While SAP relies on data that is mainly supplied by customers and users, SugarCRM with Node relies on data that is mostly totally external to a company.
The acquisition of Node pays well into the SugarCRM story of the time-aware data model and the no touch information management. The time awareness is brought forward to not only cover and analyse changes that occurred up to the present time but also now covers the ability to predict with what Node calls its Artificial Intuition™ technology. The no touch information management story is strengthened by accurate predictions returning from the AI subsystem that deliver value to the users by being immediately actionable. There is no further data entry needed. Of course, and that always needs to be said: The better the basis of existing data, the better the AI. There is no free lunch here.
So, there is a lot to expect from this acquisition. SugarCRM customers will see a lot of exciting new capabilities through the course of the next twelve months. Last year, I asked whether SugarCRM gets its mojo back. This year, I can say, it gained a lot and is on its way to get even more.