Today’s post is by Matt Langie, CMO at XANT.
We have all seen enough Hollywood movies to know the stereotypes of sales. The sunburned door-to-door suspect. The slicked-back smooth talker at the car lot. The buttoned-up professional in the boardroom. Among the more recent additions is the caffeine-driven tech bro working the phones and email.
Good Sales Leads Always Drive Revenue
But the one thing these caricatures tend to get right is the driving need for good leads. Good leads have always been the backbone of any sales organization to build pipeline and drive revenue.
With each new technological revolution, the way sales teams found, sorted, and pursued leads improved. The humble act of knocking on doors drastically decreased as more households adopted the telephone. Cold calling began to disappear as computers helped teams find better targets and communication preferences shifted from phone to email.
However, even as more sales representatives adopt digital communication, they struggle to get the right data to do their jobs. This is where artificial intelligence (AI) can take sales to the next level. AI is not just a reworking of tried-and-true technology; it is a genuine game changer. Companies that utilize AI to drive sales leads are finding that it does more than just level the playing field – it raises the entire field. These companies are becoming more efficient and reaching more of the right prospects, at the right times, in the right ways.
Find Sales Leads More Efficiently with AI
There are three primary ways companies can reap the benefits of AI for sales:
- Implementing data algorithms that comprise the right statistical and machine learning code that helps an AI learn data patterns.
The right data algorithms can fuel automation capabilities to improve the sales process. Those same algorithms can also enable automation to improve a sales rep’s visibility and productivity. Utilizing these algorithms correctly breaks down which sales activities will have the greatest impact, at the right time of day.
- Gathering enough data volume and depth of information so AI algorithms can sort, compile, and understand these inputs.
CRM and sales activity data can be merged, anonymized, encrypted, and enriched. Once complete, that processed data can be used to train AI models that deliver predictive insights to sales organizations. This will help sales reps target the right customers – improving the quality and effectiveness of any given engagement.
- Ensuring proper data quality – including variability, freshness, and uniqueness – so AI can provide the best outputs.
By enriching and extending customer data, an AI system can best identify not only whom to target, but, more importantly, how they behave and how to best engage them.
This enables every sales representative to effectively execute a “cadence” when they reach out via email, phone, social media, etc., to initiate a conversation with a potential prospect. The art of a cadence is determined based on myriad factors, fueled primarily by the quality of data regarding the company and contact being pursued.
These three levers help sales teams produce exceptional data intelligence and, in turn, more sales. The intelligence behind these levers is also not new – essentially, sales leads have been driven by patterns, raw data, and quality for many years. But AI helps leverage much larger datasets than ever before, find the best variables and fit, and then predict business outcomes with high accuracy.
Imagine a world with no more cold calling and fewer leads that turn out to be duds? Imagine a world where you’re not wasting time and resources selling to the wrong individual at a company? Using AI to improve leads and manage the sales team will make everyone from the EVP of sales to the junior associates happy, which will turn around the stereotypes and present a kinder, gentler form of salesperson. Where will scriptwriters turn in the future for examples of burned-out, frustrated professionals? Maybe the marketing team.