Precise sales forecasting and automated lead scoring using AI will lift the performance of your agents and bring precision to your business growth projections
Sales forecasting is critical to long-term business growth but the majority (69%) of companies find their current efforts ineffective. This is a result of the various methodologies in use which range from in-depth historical analyses to gut feeling assessments.
Weighted pipeline forecasting is the most common method and employs a linear model. It involves assigning a percentage likelihood of a deal closing to every sales opportunity in the pipeline (in relation to its stage in a company’s CRM) and multiplying it by the revenue value expected. The sales forecast is the aggregate sum of all revenue values.
The problem with the weighted pipeline is its failure to address that selling is a zero-sum game. If an $80,000 deal is in the qualification stage and its close rate is 25%, its value is $20,000. However, practically, there is no scenario where the deal would result in $20,000 in revenue.
There has never been a greater need to understand the pulse of business. Shareholders and board members are uncomfortable with surprises. They expect controlled performance from their executives. Analysing forecast accuracy can reveal selling, personnel or negotiating issues, which, when addressed, will help a business improve its forecast accuracy.
Clearly, the need for greater accuracy exists and this is where Impact AI comes in. Impact AI addresses the flaws inherent in traditional forecasting methods including the widely used weighted pipeline.
IMPROVED SALES FORECASTING, BETTER GROWTH
Companies with more accurate sales forecasting are better at growing their year-over-year revenue and are more likely to hit quota. Misleading buying signals are at the root of inaccurate lead scoring. It’s a widely acknowledged problem reflected by a 2016 study that reveals 61% of companies highlighted “misleading buying signals” as the biggest challenges in accurate lead scoring. It explains why only 40% of sales teams believe lead scoring adds value even though the majority had implemented them.
Impact AI offers a reliable solution to the problem of forecasting sales opportunities through its ability to analyse large volumes of real-time and historical data to identify the best leads. Impact AI’s Automated Lead Scoring function is more accurate than traditional methods because it employs sophisticated non-linear models which are both interpretable and explainable.
It also uses Ensemble Learning in combination with Machine Learning (ML) and Continuous Learning to reveal the hottest leads from the demographic, firmographic, and technographic factors collected.
At present, less than half of all sales opportunities are converted. Ensemble Learning methods use multiple learning algorithms to drive a better predictive performance than is possible from any of the constituent Machine Learning algorithms alone. When combined with Continual Learning, it enables autonomous incremental development of ever more complex skills and knowledge. When applied to Automated Lead Scoring, it results in a higher percentage of conversions because more effort focuses on the best sales opportunities.
As your business grows, your lead scoring needs to scale and your agents need to give the most attention to the most important leads. Automated Lead Scoring in combination with Automated Lead segmentation performs this function.
Ultimately, Impact AI enables agents to focus on the best lead and approach at the most opportune time while equipped with the most effective sales information.
REDUCE CHURN BY RESPONDING TO MARKET INFLUENCES
Every business appreciates the importance of retention and a significant reduction in churn rates is possible through applying AI. Existing customers are often the biggest source of revenue for most companies. By comparison, it is four times more expensive to acquire a new client than to upsell to existing customers. Despite this, too many businesses struggle to pair their products with customer need. This is partly explained by the fact that over one third fail to track their customers’ journey.
Impact AI enables a sales team to respond to influences in the market. By tracking the customer journey, agents are aware of the experience – both positive and negative – clients have in real time. Armed with insights about sentiment, preferences and other buying triggers, an agent moves from solution selling to insight selling.
Businesses operate in a hyper-connected world which requires immediate action when a complaint arises. Research reveals that 25% of customers will not return after just one bad experience. Chatbots enable every business the opportunity to engage with customers 24/7/365 and respond instantly and when it suits the client most.
Impact AI monitors customer activity patterns to proactively identify issues before they escalate and significantly reduce churn and increase retention.
Breaking free from forecasting through historical sales data and other traditional parameters is the only way to improve accuracy. Customer behaviours, market conditions, and competitive forces have an impact on sales performance but are often left unaccounted for. Impact AI pulls together factors and updates their influence through Machine Learning to enable agents to see a lead’s value.
AI’s influence on business is growing and will continue to grow. The benefits of adoption are undisputed as are the consequences of sticking with past methods.