SugarCRM_Node

SUGARCRM acquires AI/AI provider Node

The deal was announced at the end of August. SugarCRM acquires Node, an AI data analytics provider. Node is “an artificial intelligence (AI) platform that leverages CRM data and huge external sources to deliver an unprecedented level of predictability across a whole range of different business applications. This acquisition supports the current CX platform or user of SugarCRM by automatically predicting suitable results and highlighting previously unforeseen challenges and opportunities.” (Translated as DeepL.com and adapted based on SugarCRM’s PR release.)

Exciting thing: unsolicited and previously unnoticed facts

We are looking forward to the first business cases. Because there is absolutely huge potential here. The vast majority of companies only partially or not at all exploit this potential that lies in the data.

We experimented with such a similar provider 3 years ago. That was not so productive at the time. But 3 years later and enriched by many experiences, we expect significantly better results.

Especially for selections within the campaign planning – “Who do you write to, who not?” – such a tool is helpful. The same applies to sales planning, which is about “who do I visit, who am I not visiting?”

It could thus save costs or help to increase sales.

SugarCRM buys Node an AI data analytics provider “… replace a fragmented, outdated and distorted image with a sharply focused image.”

“Obtaining a high definition view of your business and customers, from pipeline to forecasting, is all about replacing a fragmented, dated, and distorted picture with one that is sharply focused and rich in breadth and depth,” said Craig Charlton, CEO of SugarCRM. “Sugar is democratizing AI, ushering in a new frontier in CX with its powerful combination of AI, time-aware and data enrichment, to drive business performance and enable predictability for companies of all sizes.”

SugarCRM Buys Node an AI Data Analytics Provider – What Does SugarCRM Promise?

  • Identify the customers most likely to migrate and provide a valuable runway to troubleshoot problems and reach customers as strategically as possible
  • Prediction of conversion probability from lead scoring models
  • Insight-driven forecasting and prescriptive guidance for increased quota reach and accurate monitoring of sales
  • Seamless recommendations for ancillary products at the right stage of the customer journey to increase average sales size
  • Determination of marketing attribution and contribution to closed transactions
  • Improve customer engagement models through predictive case routing and real-time contextual data to empower customer service representatives

As mentioned above, we are looking forward to the first practice cases. Because, if that works, that would be a big lever. In this respect, it is also an interesting question whether the typical user can cope with the functions of Node or whether a specialist is needed who still has to process and interpret procedures and results?

More about SugarCRM on CRM-TECH.World

Who is behind SugarCRM?

SugarCRM in the Gartner Magic Quadrant

 

Note: This is a machine translation. It is neither 100% complete nor 100% correct. We can therefore not guarantee the result.

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