In the words of Pearl Zhu, ‘We are slowly moving into an era where big data is the starting point, not the end.’
More and more businesses are using AI today to predict customer wants and needs. The AI-powered recommender system from Amazon has revolutionized the e-commerce experience today. Here’s an example:
Netflix uses a great recommendation algorithm that identifies the choice patterns of its users and saves them $1 billion annually from subscription cancellations. Uber uses an AI-backed location algorithm that optimizes the customer’s location, makes sure the car follows the fastest route, and enables seamless service.
With so much competition in every sphere of business, using AI to make data-driven decisions can exponentially boost business revenues and mean the difference between success and failure.
Five ways to boost sales
1. Discounting & pricing
A Salesforce survey has revealed that only 25% of the surveyed companies use AI-backed predictive analytics, but nearly 85% of them have seen an enhancement of ROI.
One of the essential areas AI can help businesses in is the decision of customer discounts. Businesses don’t want to overcharge a lucrative customer and lose them. Nor can they afford to undercut their service fees.
An AI algorithm that’s fed with the details of similar past deals can identify and advise on the discount rate that’s most likely to be a win-win situation for both parties.
Some of the essential details that are usually needed to make such a decision are:
- The dollar price
- Service/ product details
- Number of deals closed or lost
- Number of players in the industry
- Average annual revenue of competitors
- External and internal influencers
- New vs. existing clientele
- An ongoing fiscal quarter (Q1 or Q3)
2. Cross-selling & upselling
Cross-selling and upselling accounts for nearly 39% of Amazon’s annual revenue. They’re very fast methods to improve the revenue since businesses don’t need to acquire new customers. Businesses can also improve their bottom-lines since getting new customers is five times more expensive than retaining the existing ones.
An AI algorithm can be highly effective in identifying the customers who are most likely to purchase a better model of a product they already own (which is upsell). Or buy something that is related to an item that they already have (which is cross-sell).
With the right algorithm, businesses don’t have to waste time and effort trying to sell to each customer. They can instead concentrate on and target the ones that are most likely to buy and improve their probability of sales.
Some of the details that an AI algorithm needs to be fed are:
- The customer’s purchase history
- The median price and the price range of purchase
- Purchase frequency
- Payment methods used
All of these are easily available to any business and can be used efficiently to boost revenue.
3. Lead scoring
In the earlier days, lead scoring and decision making in sales were made manually. Employees had to juggle between customers and, under perennial time pressure, frequently made the wrong decision as to which lead had a better chance of a conversion. It was more of guesswork based on gut feelings.
The AI-algorithm of today can access and analyze extensive details about the customers, like:
- Purchase history and pattern
- Social media posts
- Customer service and website interactions
- Email open rates
The algorithm can immediately score the purchase feasibility for every customer and rank them in any desired manner.
With optimal lead scoring, the salespeople do not have to worry about choosing the right customers, and can instead focus solely on selling their products.
You can even use plenty of tools for automated lead generated and scoring. On top of that, you can take assistance from plenty of automated AI tools like the digital adoption solution by Whatfix. Such platforms come in handy to help you adapt to and work with multiple automation and marketing tools.
4. Revenue forecasting
The primary source of revenue for any business is product/ service sales. Every operational, tactical, and strategic planning decision of a company depends on its present and future sales figures. Without a proper sales forecasting protocol in place, key business decisions are hampered.
Some of them are:
- Number of promotions to be handed out
- Number of new hires required
- Employee layoffs (if any)
- Contract renewals
- Need for new business partnerships
A few decades back, this was done manually.
Today, the powerful AI algorithms can analyze industry trends and metrics like year-on-year quarterly revenue changes, pipeline coverage, previous sales quota and attainment levels, and sales activity data, both on local and global levels.
It can then accurately predict market shrinkage or growth and uncover hidden sales patterns that are difficult to unravel otherwise.
5. Performance management
The salespeople are the ones responsible for the influx of revenue at any company.
However, no one really knows for sure how many of them are actually going to hit their monthly sales quotas. Most businesses have to wait till the month-end to find out.
The problem with such delayed information is that it prevents managers from nurturing the actually interested leads down the sales funnel towards making a sale. This, in turn, stalls the company from meeting its quarterly and annual sales targets.
With AI algorithms, managers can monitor various metrics for individual salespeople on their team and find out how many are most likely to meet their respective targets.
Some of them are:
- Opportunity-to-win ratio
- Conversion rate
- Average deal size
- Average days to close
- Historical performance data (monthly, quarterly, and yearly)
- Percentage of months when sales targets met
The algorithms can analyze these datasets and predict which individuals are most likely to meet their respective targets in a particular month or quarter. This provides time to the leadership team to streamline their attention in a targeted manner to the salespeople who have the highest chances of conversion.
Jeffrey Gitomer once said, ‘Great salespeople are relationship builders who provide value and help their customers win.’
Amidst the intense competition in the business world today, the focus is well and truly on value-based selling in a setting where relationships matter. 79% of buyers opine that they’ll buy from someone they trust, as long as it adds value.
With increasing focus on the customer journey and sales experiences, today’s AI algorithms help businesses curate the perfect sales journey for their prospective leads.
Externally, they help companies provide interested customers with the products they want, designed just the way they desire it.
Internally, they enhance managers’ ability to make informed decisions based on hard facts and eliminate chance and guesswork.