Product, process, and people are all critical to business success. Outcomes can be precisely steered when analytics are applied to previously unseen, unharvested data across all business activities and drivers. Data, analytics, tools and data scientists (the people most qualified to help) are integral to how well a company leverages data. 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 for certain disciplines 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 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 will evolve across all channels. A b2b, b2c sale or otherwise is ultimately about a successful conversation. Remote conversations are here to stay, their success rates are taking on greater significance.
The resulting analytics from a recently built predictive sales model - conducted by a progressive conversational analytics venture - containing 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 quality of job fit this represents one of the biggest points of leverage for the 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 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 b2b, but not typical in b2c 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 in only 1% of all calls - there was a 70% conversion rate. For most b2c companies, getting sales reps to regularly use some of these techniques can translate into a great improvement in revenue generation.
The potential insights from this new, relatively untapped data source are broad. Companies have found find that a large segment of clients calling into their queue were enquiring about products not offered by the company e.g. In an insurance company specific vehicle insurance (RV) their competitors offer. 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 that was prevalent in so many facets of business has shifted as data and resulting insights are delivered at speed enables bold leaders to make insightful decisions, and correct mistakes at speed. Great advances in technology now allow sales leaders to gain a deeper level of insight into performance. Product and process help people to determine approach, and how they might position and carry out tasks to increase productivity, and to know they have the right people executing. All the productivity hacks, enablement tools and tech stacks will only improve the productivity relative to the potential of the people in the seats. Poor fit personnel, in roles they are not innately suited to perform well in will always result in suboptimal results.
At Lavan we enable data-driven business models. Data utilization creates measurable added value in all layers of forward-looking companies. We help secure the future viability of companies through data-driven products, services and business models along the entire value chain.
Successful data usage (should) drive the purpose of all businesses. In sales for example it can provide (near) real time insights, which products and services of the company are consumed when, where and by whom. It should help guide the strategy to find the optimal price of the service and product. Sales, lead generation and marketing functions are intersecting extremely closely both in terms of purpose and timeline. CROs are abundantly aware of the need to leverage the entire value chain roles and data. With an internal open data strategy, data is made available for everyone in the company to base decisions on evidence and continuous improvement.
If data is business driven, then it doesn‘t need infrastructure in order to start, but a business case. Starting from here, solve the business challenge first and then, if there is value for the company, start thinking about the data engineering, technology stack and data governance. The saying 'form follows function' is not only true in architecture, but especially in data driven business development.
A clear and present impediment to sustainability for most small, medium and even larger business enterprises is lack of data, analytics, and access to 'data scientists' to help drive data strategy, and invaluable insights.
Data scientists are not only in demand, and in short supply they are costly. Often, the diverse teams that maybe necessary to cover broad business challenges are only afforded by enterprises with deeper pockets. Our Data Scientist as a service changes that. A deep bench of leading data scientists deliver a suite of diagnostic, descriptive, predictive and prescriptive services to aid underserved SME communities. In defined project work, clients benefit from a team of expert data scientists in the same way fortune 500 companies do.
Reach out to start a conversation about how data, analytics and DSaaS can enable your company to achieve a sustainable advantage.