AI for Sales
Tags: ai, sales, news, datascience
Published: 2022-05-27 10:16:38


_Smart technology has revolutionised the world as we know it and gets smarter with each passing hour; where do salespersons stand? How is technology changing the way salespeople do business?  What are the unseen consequences in sales or business if salespersons do not adapt to the Fourth Industrial Revolution? Like many other industries, the world of sales and marketing is experiencing a significant change - ‘tectonic shifts. Thanks to the cutting edge digital infrastructure, Artificial Intelligence (one of the advances of the Fourth Industrial Revolution) has a global footprint, I.e. in every industry. According to a study conducted by [Harvard Business Review](https://research.aimultiple.com/ai-stats/#sales), companies using AI in sales increased their leads by more than 50%, reduced call time by 60-70 %, and realised cost reductions of 40-60%._ 

Artificial Intelligence has revolutionised sales departments in companies, and at present, companies boost their lead volume, improve rate, and supercharge overall sales performance. AI algorithms can help power any company’s decision-making process and make better business predictions.
 
According to “**Sales Ex Machina** - _How Artificial Intelligence is Changing the World of Selling_” by _V Antonio and  J. G Anderson, PhD,_ there are five specific areas where AI algorithms can be leveraged by sales teams hence growing your businesses. - Lead Scoring, Price Optimisation, forecasting, upselling and cross-selling, and managing performance (_Using this book as a basis for my research_)

### Deal Closure and  Lead Scoring
When closing deals, a salesperson with a rich pipeline of potential clients have to decide where to focus their time to close a particular deal.  Often, salespeople make decisions based on their intuition and incomplete information. Using AI, data scientists compile historical information about a client, company, social media postings and the salesperson’s customer interaction history  (e.g. emails sent, calls made, text sent etc. ); and rank the opportunities or leads in the pipeline according to their chances (probability) of closing successfully.  One tool built on this methodology is [Dealcode GmbH](https://www.dealcode.ai/?) with the slogan **TIME KILLS DEALS!**

> [Dealcode](https://www.dealcode.ai/?) is an AI guided selling software tool that determines the winning probability of the prospectus as well as the risk involved in a sales pipeline. Using data from [Hubspot](https://www.hubspot.com/) and [Pipedrive](https://www.pipedrive.com/) and information from a web crawler, it provides sales team with up-to-date information on what deals they should focus on and whom they should talk to ‘today’. Their _patented_ machine learning model analyses over 150 attributes to determine individual factors that contribute to the success or failure of the sales team, hence making the sales measurably more effective 

> _A web crawler_ is an internet bot that systematically browses the world wide web using keywords.

### Price Optimisation
Using AI to tell what an ideal discount rate should be for a proposal to ensure that you’re most likely to win the deal by looking at specific features of each past deal won or lost. These features may include the size of the deal, product specifications, number of competitors,  company size etc. 

### Demand Forecasting
Using AI to forecast clients’ demands by analysing past data. This helps companies optimise their supply chain, sales and marketing operations, preventing under-stocking or overstocking.

### Upselling and cross-selling
Using AI to identify which of your existing clients would buy a better version of what they currently own and/ or which- would likely want to buy a new product offering altogether, increasing revenue and a drop in the marketing costs.

### Managing Performance
Using AI to identify the likelihood of a salesperson hitting their quotas and which outstanding deal stands a good chance of being closed. This allows managers to focus their attention on key salespeople and associated deals that would help the company hit their quota.


The accuracy of the predictions depends on the system and the quality of the data used; the AI systems need the proper inputs from the past and the present to draw conclusions (insights) and create predictions.
 
Companies always look for ways to increase their revenue, cut back on costs, and expand market share while significantly minimising risks. Leveraging existing information on clients, vendors, and web crawling enable leading companies to analyse and generate actionable insights that help their sales team close more deals.