In a digital world companies need to utilize technology, knowledge, computational power and access to data, whilst recognizing that insights are the new business currency.
New dimensional views across all business activities and their interdependencies drives the insights necessary for business sustainability. In the new digital paradigm change is constant. Data, and in real-time or as close as possible is necessary to stay ahead.
Advances in technologies like automated speech recognition, natural language processing, and machine learning now make it possible to look at huge samples of unstructured sales call data, and be able to know with greater certainty and precision what techniques sales leaders should invest in across their sales teams.
Research from conversation analytics shows that these four skills are highly predictive of closed sales in an inbound B2C environment.
- Disqualify poor opportunities
- Driving customer decisions
- Revealing objection
- Mitigating the risk of a purchase decision
The inbound call center has always been a significant revenue channel for B2C companies. The pandemic has exacerbated the importance as companies look to make up for the decline in external sales meetings. As we move through the pandemic hybrid sales models are evolving across all channels. Ultimately, whether B2B, B2C or otherwise all sales require a successful conversation. Remote conversations are here to stay, their success rates are taking on greater significance.
Results from a predictive conversational analytics sales model ingesting data from more than 8,300 independent variables, tested against a data set of roughly 2.5 million sales calls from a dozen companies provides some interesting discoveries and insight.
A hallmark of high-performing B2B salespeople selling complex solutions is they don’t pursue poor fit prospects. Instead, they aggressively disqualify bad-fit opportunities from their pipelines in order to free up time to concentrate on those deals that have a real chance of converting
High performers look to actively engage customers to surface unarticulated objections so that they can address these concerns head-on and overcome them.
Converting casual shoppers into buyers is where inbound sales are won or lost. Besides the quality of job fit, meaning the talent to perform in the role this represents one of the greatest points of leverage for a sales organization to boost performance.
High-performing sales agents focus less on diagnosing customer needs and more on prescribing solutions to customers offering personalized, prescriptive guidance to customers. "Personally, I would choose this package, or here is the plan I would go with" had the greatest positive impact on conversion rates.
High performers know that taking orders from willing buyers is easy, but what really separates them from others is their ability to convert more on the fence shoppers into buyers on a short call. If you win on the margins you normally win overall; competitions, elections, sports, and in business...
Even when reps have prescribed a perfect offer to the customer and dealt with their concerns and objections head-on, clients may still need direction to get them to commit to a purchase - particularly when a call starts with some level of purchasing reluctance and customer predisposition to take more time to mull over buying.
The sales improvement opportunity from using these 4 techniques is compelling. Often seen in B2C, but not typical in B2B sales calls;
16% of the calls looked at showed none of these "high-performer practices" being demonstrated. In those cases, conversion rates were poor. When all of these approaches were used, the study revealed there was a 70% conversion rate, unfortunately it was only in 1% of all calls. For most B2C companies, getting sales reps to regularly use some of these techniques will translate into a great improvement in revenue generation.
The insights from this new, relatively untapped data source are broad and compelling. Companies have found that a large segment of clients calling into their queue enquired about products not offered by the company e.g. An insurance company fielding requests on specific vehicle insurance (RV) they do not offer, but competitors do. Companies launching a new service or product found they can leverage sales call data to understand which competitors customers speak of most, and apply the insights in their positioning, branding and new offer messaging.
As digital transformation continues, the guesswork involved in prior years is shifting as actionable insights from data delivered at speed provides greater alignment and improved results. Advances in data and analytics allow companies, employers and employees to gain a granular, deeper level of insight into performance improvement.
Enabling data-driven business models.
In sales for example as we have seen it can provide (near) real time insights. It can tell us which products and services of the company are consumed when, where and by whom. It can help guide strategy to find the optimal price of a service and product.
The nature of real time insights is drawing the intersection of roles and function ever closer blurring and redefining responsibilities, and accountabilities. Adopting a data science approach helps unlock the power of AI for all business users.
With an internal open data strategy, data can be made available for everyone to collaborate for evidence based decisions and a cycle of continuous improvement.
Delivering actionable insights of course has the greatest impact if the people in the seats executing are best suited to perform. The demands of any roles are contextual, based on a broad ecosystem from Company, culture, product/services, and process, to industry, and or niche, a customer's buying persona all impacting what best mix and weighting of skills, experience, knowledge, traits characteristics (innate wiring) drive greatest performance.
Enablement stacks and productivity hacks, coaching and training results are magnified when the personnel performing are a good quality fit. In sales and roles where quantitative metrics represent performance, people science and performance data reveal which candidate will perform pre-hire and how to optimize post-hire.