According to Bank of America Merrill Lynch, the artificial intelligence (AI) market is projected to grow to $153 billion by 2020. If you’re in sales, this probably doesn’t come as a surprise; science has been changing sales as we know it with the recent growth of predictive analytics, prescriptive insights and more.
However, the evolution of AI in sales has resulted in a slew of new and sometimes confusing vocabulary words. That’s why we’ve compiled the below glossary, which breaks down all of the AI-related sales terms you need to know to navigate this brave new world.
Artificial Intelligence (AI) refers to the ability of computers to analyze information, accomplish tasks and make decisions like a person would. Some of the most notable traits of AI, derived from the components of human intelligence, are learning, reasoning, problem-solving, perception and language understanding.
The fuel of AI. Big data refers to the vast pool of information created due to the explosion of digital and the continued growth of social networks, connected devices and mobile technology.
The first evolution of sales intelligence. Descriptive data describes what is happening with your sales performance at a given time in response to a particular query.
Dimensions are all of the factors or variables that impact and make up a sale. Examples of dimensions include sales team, stage duration, company vertical, lead source, deal size, etc. Segmenting your sales pipeline or deals by various dimensions can uncover underlying trends, patterns or variables affecting your sales growth.
Machine learning enables computers to learn without being explicitly programmed. It works by searching through large volumes of data to identify patterns and then applying what has been learned to new data.
Natural Language Processing
The ability of computers to decode and understand the meaning behind human language patterns over time.
The second generation of sales intelligence. Predictive analytics uses historical data and machine learning capabilities to anticipate what will happen in the future, providing capabilities around lead scoring, sales forecasting, email sentiment and more.
The third and most recent generation of sales intelligence. Prescriptive insights provide specific recommendations as to the actions that can be taken to achieve particular sales outcomes. They are derived by dynamically codifying and analyzing millions of data points at once to isolate the key dimensions impacting your sales performance.
Provides a consistent and reliable way to measure and evaluate your sales strategy over time across key conversion points needed to turn a lead into a closed deal. While each company has its own unique iteration, the baseline formula and definitions for its variables is as follows:
L x %LW x %LWC x %OW x %WR x Avg($Deal)
L: Number of Leads
The total of leads that have been generated by marketing or sales but have not yet
been qualified for the sales pipeline.
%LW: Percentage of Leads Worked
The percentage of leads that has been acted upon by sales.
%LWC: Percentage of Leads Worked Converted to Opportunities
The percentage of worked leads that have been converted to opportunities (or “deals”) and have been identified as having revenue potential.
%OW: Percentage of Opportunities Worked
The percentage of opportunities that are actually worked by your sales team and
continue to the next stage of the sales pipeline
%WR: Percent Win Rate for Worked Opportunities
The percentage of worked opportunities that become won deals, or customers.
Avg ($Deal): Average Deal Size
The sum of all new sales revenue in a given period of time divided by the number of new
customers or deals.
A unique codification of a company’s historical sales data and activities. The sales genome provides the basis for deriving prescriptive insights into which factors or dimensions should be measured and monitored most closely within the sales pipeline and process, and what specific levers can be pulled to improve results.
Structured data refers to information that is highly organized and can be captured in predefined database fields, such as first name, last name, email address, company name, etc.
Sales intelligence leverages the latest in data processing and artificial intelligence to uncover insights with the potential to inform decision-making and guide sales performance.
An emerging field of sales dedicated to accurately measuring, scaling and refining growth using a distinct combination of formulas, analysis and tools designed to uncover actionable, quantifiable insights.
A sales and data expert who helps establish effective sales processes, drive team adoption, develop a unique formula for success and generate actionable, quantifiable insights.
Unstructured data encapsulates all of the data that cannot be neatly packaged in a predefined way, and represents the majority of big data. Examples of unstructured data include voice recordings, emails, social media postings and much more.
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