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How Artificial Intelligence is Disrupting the Sales industry

August 2, 2022

AI Guided Selling

How Artificial Intelligence is Disrupting the Sales industry

Artificial Intelligence can increase business revenues by up to one third and help Salespeople to automate many tasks and processes to produce better results.

AI Guided Selling, Artificial Intelligence, Machine Learning, Smarter Sales, Sales Future,

With the fourth industrial revolution, emerging technology breakthroughs in fields such as Artificial Intelligence (AI) and machine learning (ML) have been revolutionising industries. In the sales industry, it is proven to increase business revenues by up to 30 percent. According to Gartner 75 percent of all companies have plans to adopt AI-powered solutions, and even more businesses are looking into using AI so as not to be left behind. With AI and Machine Learning, salespeople can automate many repetitive tasks and processes and focus on the bottom line to produce better results.

Why does Sales need Artificial Intelligence?

Essentially, CRMs haven’t changed much since their introduction in the late nineties, such that it still requires the end user to log into the application they’re working with, create and manage tasks in the software (e.g. log calls, emails, create reminders, move leads down the pipeline, etc.), all this manually. Many salespeople find this job tedious and time-consuming; according to a study by Gartner, 42% of the CRMs go unused, and a study by Forrester shows that 47% of CRM projects fail.

That’s why some companies have already been using AI and machine learning to make CRMs work. Some of AI incorporated capabilities in CRMs include:

  1. Using pattern recognition with CRMs, analysing your most valuable deals based on specific data points is possible. It then can compare them to potential prospects and predict the values of new deals. This allows salespeople to relocate resources more appropriately based on deal value.
  2. Using AI, your business can analyse previous deals and show why a deal did not go through. Now you can see the early warning signs of potential deal churn.
  3. AI can improve sales team productivity by gaining new insights from past sales data and trends, reducing manual analysis and saving time and resources.

Artificial Intelligence Guided Selling

One emerging use of AI is channelling the data collected in CRMs (CRMs acting as a data warehouse) and using AI capabilities to analyse trends and deduct insights from this data away from CRMs. This is one of the many new methods businesses use to attract new customers. Using the general AI-based deal scoring - with the cliche that “data does not lie.” :

  1. AI can detect patterns and trends in large volumes of data sets and analyse them based on different criteria; these patterns and trends in large data sets are not visible or are hard to get without substantial computational power.
  2. The AI predictions are based on data and insights formulated based on past trends and behaviours.
  3. With an increase in historical data, the AI scoring gets better and better; the Machine learning algorithm learns from the past data to perform better.
  4. With AI deal scoring, there are no external influences; hence less error-prone. Therefore the insight is data based with influences hence a more reliable prediction.

What companies utilise data stored in CRMs? What potential do these companies have in this fourth industrial revolution age?

Dealcode is an AI Guided Selling Software that extracts data from CRMs, running its own patent machine learning algorithm. It provides an AI-Based deal scoring capability as a method companies can use to rank leads based on their closing successfully potential. Using manual deal scoring methods (methods most businesses use) is flawed and likely to cost you more than you bargained for.

How does Dealcode’s deal scoring work? Why do companies need better and more reliable deal scoring processes? It's well known that deals vary from one another, be it the client's need, engagement, behaviour or even their demography, and all these factors affect the end results. With a better and more reliable deal scoring process, Dealcode’s machine learning algorithms are continuously trained to achieve better results. This deal scoring system helps your business realise its likelihood of closing deals and the risks involved in the deal. Using past deal information and other deals, the system can predict the results of a deal in question, ensuring maximum accuracy as it is solely data-based.

Not sure what deals are the best to follow? Would you, as a salesperson, want to save time? To save your time Dealcode’s main features include CRMs (Hubspot and Pipedrive) integration, deal manager (showing deals at risk, deals to watch, new deals, open and closed deals), smart ToDo’s and AI analytics (deal winning probability over time), among others. In summary, Dealcode offers excellent features that businesses can employ to better their companies’ revenue and hence better their financial position while saving time.

Positioning your company to be sustainable, predictive deal scoring is advantageous and a must-have capacity. It has taken over much of the heavy lifting when analysing data and determining which prospects are most likely to convert. Focusing on the most vital prospects possible means that sales reps will be able to close more deals in less time while building stronger relationships with clients.

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