AI is revolutionising lead qualification
Historically, companies were at a loss when it came to analysing top of funnel buying behaviour accurately. This is largely because lead lists consisted of arbitrary information that painted distorted images of prospects, leaving sales teams to fill in many important gaps in the information loop. Fortunately, times have changed and companies are far better equipped than their evolutionary ancestors of just a few years ago.
Yet, with so many new touchpoints and customer channels arising, lead qualification often still feels like a hopeless shot in the dark. And since top of funnel prospects typically reveal little about themselves during initial engagements, marketers often miss out on key behaviours that could indicate a sale-ready lead. This causes good prospects to be overlooked while sales teams battle to make headway with the contact list they’re given.
Data-driven lead qualification is bringing prospects into sharper focus
Fast-evolving AI and machine learning algorithms are helping sales and marketing teams engage elusive prospects more contextually than in days prior. They do this by accurately picking up on signs that indicate a shift in a prospect’s readiness to enter the buyer’s journey.
For example, information such as new investment capital, an increase in staff count, new technology adoption or a new executive hire can help to paint more accurate pictures around a B2B lead’s propensity to purchase. These insights enable sales and marketing teams to engage prospects that exhibit often overlooked indicators more effectively.
Excitement amongst marketing and sales execs around AI and machine learning is well founded as the technology’s potential to revolutionise entire industries is fairly demonstrable. Over 70% of respondents in an Economist survey stated that AI will be implemented within their business in the next three years and more than ten percent are actively investing in the technology in some form.
“Fifty-five percent of CMOs across five global markets think AI will transform the marketing landscape even more than social media.” – Weber Shandwick
Predictive analytics models can help companies identify quality leads over weaker ones earlier in the buying cycle and thereby allow them to focus on high stakes prospects. Historically, much time was spent working through contact lists, repeat calls, unanswered emails and fruitless meetings while good leads slip through the cracks. New sales and marketing tech is changing that by taking passive information from CRM and other information systems to make new and interesting correlations from lead data – which sales teams may not have made otherwise.
Getting more out if your data for improved lead scoring with AI
While CRM and automation systems have their rightful place in the marketing and sales continuum, they don’t deliver the insights sales teams need to identify the best leads in their cache of contacts. And with an increasingly fickle market that demands more personalised customer experiences, getting to grips with top funnel leads becomes increasingly tricky. Further, the absence of the right tools to uncover opportunities within that information can make things even murkier.
By applying predictive models to lead data, marketing teams know they’re passing on sales-ready leads that are most likely to convert down the funnel. And as those leads traverse the sales process, more information is collected and subjected to analysis for more adaptable and personalised conversion paths. This data-informed approach can take many forms; from search driven analytics that allows users to explore customer data, to speech analytics that inform sales reps’ conversations with new leads. AI in its many forms is influencing the customer and lead engagement process on various important levels.
“AI continues to drive change in how businesses and governments interact with customers and constituents.” – Gartner
The cost incentive for AI-based sales models is compelling
By reducing the time and human resources required to qualify and move leads down the sales funnel, AI is helping to reduce overall marketing and sales budgets. This, in conjunction with the up in revenues companies can expect from an AI investment makes the case for adoption a strong one. Hurdles to new technological adoption are also being addressed by easily deployable cloud-hosted platforms that make migrations to analytics platform relatively seamless – compared to migrations of yesteryear.
With most back office administration and technical management of AI applications taken care of by vendors, companies can focus their attention on interrogating their datasets and understanding how to derive value from it. This “just add your data” model of machine learning is making the move to data-driven marketing more possible for more companies.
Close the sales loop with Synoptica
At Synoptica, we believe in the power of data to inform critical business decisions that result in increased business performance, higher profit margins and better ways of working. Our AI-based sales analytics platform takes a wider view at your leads to deliver unique insights that inform you about crucial buying signals from high quality leads.
We go beyond collecting standard or arbitrary intelligence on your leads. Instead, we augment existing information with contextual and correlative data that enriches your customer insights and informs marketing and sales strategies across the board. To find out more about how we can help you improve you lead qualification with the power of AI, contact us today.