November 5, 2021

Written by

Collective[i] Team

  • Posted in
  • Prescriptive Forecasting
  • Artificial Intelligence
  • Neural Networks

Gartner case study on Collective[i]: The future of intelligent applications

By 2025, 60% of B2B companies will have transitioned from dated intuition-based selling to data-driven selling, according to the industry-leading research company Gartner. To meet the demand for these needs head-on, Collective[i] is modernizing data-driven sales through the power of technology, artificial intelligence (AI), and shared intelligence. In today’s fast-paced market, leveraging the kinds of technology and tools that can analyze data and provide real-time, dynamic insights to sales teams can frankly be the difference between success and failure.

Recently Collective[i]’s co-founder and vice chair, Stephen Messer, was interviewed by Gartner as a part of its Future of Technology Research Project. With over 40 year of experience providing insights, Gartner is known for sharing quality, objective research about business practices that are defining the future. Their case study on Collective[i] explores why intelligent applications are the future of technology and how Collective[i] is leading the charge on providing intelligent, networked cutting-edge tools to the B2B industry.

While information has always been central to business, Messer says that “The future of work is about enabling agile and highly targeted execution that adapts to market changes and customer preferences. Intelligent applications are the underlying technology enabling this transformation.” This article will explore how these applications use networked data to drive sales and revenue optimization, and why B2B organizations need to embrace this technology to ensure their strategy is future-proof.

Intelligent applications: The future of sales

Until recently the business world has operated on a “you only know what you know” system, using internal data sets — and perhaps some publicly available market data — to attempt to anticipate the market, understand buyer needs, and train A-lite algorithms. Yet this approach is problematic; it’s nearly impossible for algorithms to predict the future and the market shifts that defy historical patterns with internal data alone. Today’s world is simply too fast-paced and dynamic to rely solely on history and intuition.

Intelligent applications actually become intelligent — that is, able to analyze patterns and make data-driven predictions — by being trained with massive networks of datasets to provide on-demand, dynamic, and personalized solutions for end-users. They work by using multiple forms of AI, like robotic process automation, machine learning, and neural networks to eliminate processes and tasks, analyze massive real-time data sets, and recommend the next and best business actions to drive efficiency and data-driven thinking. The bottom line: all of this ultimately allows companies to better manage and grow their revenue.

The datasets that intelligent applications use can be divided into two categories: narrow and networked.

  • Narrow datasets come from a single company, including historical sales data and customer journey statistics. Essentially, data that companies have historically relied upon.
  • Networked datasets are drawn from a collective of companies, each contributing its information in exchange for the valuable intelligence derived from the anonymized information from a network of companies.

The real value of networked data

Traditionally, applications — even those that sold themselves as “smart” or AI-lite — have been limited to a company’s historical, narrow datasets, which severely limits the recommendations and insights they can provide. This is especially true in new or volatile markets where there’s little history or it’s incredibly complex. In other words, the kinds of markets where B2B companies operate.

And that’s where networked data shines. These networked datasets are massive — both in their size and in their diversity and reach outside of what a company already knows. Networked data adds depth, breadth, and dynamic, detailed insights to help sales teams make smarter decisions and focus on the actions that are most likely to have the desired results — all thanks to huge networked data sets and the information they provide.

The B2C world embraced the value of networked data and intelligent applications years ago, illustrating how transformative this process can be. Tech giants like Amazon, Netflix, and others became as skilled as they are at understanding consumers in part because of vast amounts of networked data and intelligent applications that can take the data and truly understand consumer behavior. For years, they’ve recognized network data for what it truly is: a critical component in staying competitive. According to Messer, “That approach gives them a leg up when they enter B2B markets — look at Amazon’s AWS and Alibaba with Ant Financial. They quickly dominated because the computing and banking worlds lacked the ability to adapt to the networked approach to leveraging large datasets and AI in time to catch up once these players entered their market.”

At Collective[i], our intelligent tools are designed to help B2B sales teams by optimizing insights, dynamic sales forecasts, and opportunity odds. Networked data is the modern solution to this challenge, providing a more accurate picture of the ever-changing markets that B2B companies operate in.

Intelligence is foundational to the future of high tech

Intelligent applications are the way of the future and companies that fail to embrace them risk obsolescence. According to Messer, “Intelligent applications require a new paradigm that dynamically learns in order to support continuous optimization.”

These applications make sales teams’ jobs easier and provide the kind of data-driven insights that can help each and every member of a sales team perform better and more efficiently, eliminating much of the friction in the B2B sales cycle with intelligent insights. Yet there’s a persistent fear that AI and technology are going to displace workers, or that technology simply can’t provide the kind of judgement that an experienced seller can. These fears, however, simply aren’t valid.

“AI is an extraordinary advancement in that it can remove processes entirely, with human talent operating at its greatest capacity,” says Messer. In other words, intelligent tools will automate the parts of a job that can — and should — be automated, and they’ll provide the kinds of insights and judgements that even the most experienced seller can’t. But intelligent applications can’t and won’t replace the higher-value work that sales teams excel at, like the communication and relationship-building tasks that are so necessary to the outcome of a sale.

Deals are more complex than ever, and it’s time for B2B companies to embrace the kind of intelligent applications that can meet the challenge head-on. Click here to learn more about how Collective[i] can help solve your needs.

Gartner subscribers may click here to read the full Gartner case study: Intelligent Applications in the Future of High-Tech: Collective[i]’s Experience. Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s Research & Advisory organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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