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    How AI Can Prevent CRM’s ‘Garbage In, Garbage Out’ Syndrome

    Written by

    Chris Preimesberger
    Published April 17, 2019
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      eWEEK content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More.

      After 20 years in business, Salesforce’s Achilles’ heel may be showing up: Failure for a growing number of companies to deliver on promised ROI for better sales visibility, sales productivity, sales effectiveness and better customer management.

      Many companies have invested millions of dollars in customer relationship management and marketing automation tools. That investment has failed to live up to expectations in large part because traditional CRM tools require users to manually enter contacts and customer activity data, which salespeople loathe and is their main productivity killer.

      In many cases, enterprises force reps to spend 30 percent of their time manually entering data–which they only capture about 20 percent, leaving 80 percent of contacts and customer activity data lost. SiriusDecisions estimated that about one day per week per employee is burned up by manual administrative tasks and even more because of lack of insight.

      Worse yet, sales, marketing and customer success teams have had to manually comb through Excel files, information silos and reports looking for insights like a needle in a haystack. This mundane productivity loss and manual search for insights wastes precious time and causes a combined 40-60 percent loss of selling capacity for customer-facing teams at large enterprises.

      Fortune 1000 companies have realized that they are not fully capturing the opportunity that their sales and marketing data and tools provided. Many are beginning to recognize the importance of data science/machine learning/AI as a core platform of their digital transformation.  

      In this eWEEK Data Points article, we offer some industry information from People.ai, which makes a new-gen revenue intelligence system that works alongside Salesforce and provides a new look at this problem.

      Data Point No. 1: Harnessing the Data is the First Order of Business

      Customers often have all of the data that they need to drive above market growth.  The real challenge is figuring out how to harness the data to drive real business insights.  They key is having the right data combined from key sources to provide the right intelligence to the right person at the right time.  Often the data is fragmented across different systems or organizational silos (or locked in seemingly inaccessible systems such as exchange server) and at other times the data isn’t even captured in the management tools.  Imagine being able to bring data together in real time such as frequency of touches with the customer, products bought, growth rate, experience they’ve had with products, rep turnover, support issues and soon.

      Data Point No. 2: Getting High ROI Out of Salesforce

      The key to cracking the code is to get the highest ROI out of Salesforce in a way that will drastically change how sales, marketing and customer success teams effectively use CRM. With artificial intelligence now a reality in more and more apps, there are companies tackling this 20-year-old problem that has plagued every company that has used CRM since its inception. Enterprises need to find solutions that can automate the capture of all contact and customer activity data, dynamically update CRM and provide actionable intelligence across management tools for sales, marketing, customer success and services teams.

      Data Point No. 3: AI’s Steep Upward Movement

      AI is on a steep adoption curve, particularly to drive greater sales efficiency, productivity, revenue growth  and more engaging customer experiences. A PwC report recently revealed that 48 percent of organizations will grow revenue opportunities and increase profits through AI, while 46 percent of companies are already leveraging it in order to improve their customers’ experiences. This is critical, since buying behavior across every industry (financial services, telecom, technology, etc.) has changed.

      Data Point No. 4:  One New Vendor’s Approach

      A new-gen cloud service provider, People.ai, said it has spent three years building an advanced revenue intelligence system that understands relationships between people and companies through business contact and activity data capture and injects that information into systems of record, such as CRM, marketing automation, business intelligence or customer success platforms, making them smarter.

      People.ai said its revenue intelligence system has learned from a $1 trillion pipeline; 350 million sales activities; 26 million contacts; 37 million leads processed; and 15 million buying group participants. There’s a lot of usable business data in those storage bins.

      Data Point No. 5: Automation is Key in Data Capture Processes

      People.ai claims that its revenue intelligence system not only automates antiquated and slow data capture processes but uses the power of AI to deliver real-time insights, best next actions and predictive intelligence to reps, managers–even C-suite execs–of large enterprises. This can unlock revenue with data that enterprises already had but didn’t have access to. People.ai said it automates the capture of all contact and customer activity data, dynamically updates CRM and provides actionable intelligence across management tools for sales, marketing, customer success and services teams.

      Data Point No. 6: What Two Analysts Contend

      While revenue intelligence is a relatively new concept, it’s been validated by industry experts:

      • Dana Therrien from Sirius Decisions: “Revenue Intelligence providers are leading the charge of delivering on the promise of what sales force automation was supposed to do.”
      • Maribel Lopez, principal at Lopez Research: “Faster time to insight means faster time to revenue. As new AI providers bring to market Revenue Intelligence and management capabilities, organizations will be able to find data from existing corporate resources and accelerate insights that weren’t possible before artificial intelligence. For customer-facing teams, including sales, marketing and customer success, this is a “game-changer.”
      Chris Preimesberger
      Chris Preimesberger
      https://www.eweek.com/author/cpreimesberger/
      Chris J. Preimesberger is Editor Emeritus of eWEEK. In his 16 years and more than 5,000 articles at eWEEK, he distinguished himself in reporting and analysis of the business use of new-gen IT in a variety of sectors, including cloud computing, data center systems, storage, edge systems, security and others. In February 2017 and September 2018, Chris was named among the 250 most influential business journalists in the world (https://richtopia.com/inspirational-people/top-250-business-journalists/) by Richtopia, a UK research firm that used analytics to compile the ranking. He has won several national and regional awards for his work, including a 2011 Folio Award for a profile (https://www.eweek.com/cloud/marc-benioff-trend-seer-and-business-socialist/) of Salesforce founder/CEO Marc Benioff--the only time he has entered the competition. Previously, Chris was a founding editor of both IT Manager's Journal and DevX.com and was managing editor of Software Development magazine. He has been a stringer for the Associated Press since 1983 and resides in Silicon Valley.
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