The Science of B2B Sales Growth

Is B2B sales an art or a science?

We’d all like to be known as cutting edge, avant-garde, trailblazers, innovators or pioneers with respect to our commercial exploits. But, in reality, many of us are still grappling with the new world order when it comes to B2B sales techniques and B2B selling strategies, as our industry becomes less about face-to-face meetings and relationships built over years, and more about data-driven insight, powered by AI, machine learning, and digital multi-channel instant action engagement.

The truth is that in 2018 B2B sales growth is more science than art, and those companies that have embraced this disruption are now outperforming their more traditionally-minded peers.

Not convinced? A recent report published by McKinsey & Company, a world leader in business research and consultancy, called What the Future Science of B2B Sales Growth Looks Like may just change your mind.

In this report they claim that B2B sales techniques have most definitely evolved from an art to a science, and they deliver many convincing arguments about why recent developments, such as the use of AI sales software and machine learning for sales, are changing the future of the profession.

In this post I will break down the report into four key takeaways, wrapped up with some of Artesian’s own insight based on our incredibly rich understanding of the enterprise B2B landscape through the eyes of our customers – some of the biggest and most influential companies in the world.

What, Why, When – the science of understanding your customers

Knowing what your customers want, why they want it, and when they want it, is and always has been a fundamental of good B2B sales strategies. But ‘what, why, when’ is no longer driven by our human understanding of what customers want based on past interactions, accumulated knowledge and gut instinct (an art form if you like). Instead it is increasingly driven by advanced analytics and cognitive-based AI solutions that utilise machine learning and natural language processing. Why? The answer is data of course!

Data is an increasingly important part of B2B sales strategies, and the availability and volume of data is growing exponentially. Humans simply don’t have the time, or mental capacity, to sift through the millions of articles, blogs, press releases, financial reports and social media feeds posted worldwide every day. Instead to combat the data and business intelligence challenge we must turn to machines.

Artificial intelligence for sales software that uses advanced analytics and machine learning to dig deeper into data sets and analyse, filter and present the actionable insights of greatest value – those that improve real-time understanding of the customer and what’s driving them at any given moment.

According to the McKinsey report, companies that have embraced the “science of B2B sales” and invested in tools to advance their understanding of ‘what, when, why’ have already started to pull ahead of their peers in terms of revenue growth (registering 2.3 times the industry average), profitability (3 to 5 percent additional return on sales) and shareholder value (8 percent higher total return to shareholders). Indeed comparative research suggests that insight-driven businesses using more advanced technologies will steal $1.2 trillion per annum from their less-informed peers.

There is no doubt that many businesses leaders remain sceptical of the use of AI in sales will deliver a return on the substantial infrastructure and software investment required. But my response would be this – what is the cost of not investing in the science of understanding your customers?

My key takeaway here is to select carefully the tools and technologies that can streamline the analytics process, discover efficiencies within your business, and cost effectively exploit ‘what, why, when’ from data to take your customer understanding and B2B selling strategies from art to science.

Lightning fast action – the science of engaging with your customers

A key message from the report is the importance of engaging with customers the way they want to be engaged with. The report points to good news for those frightened for the future of the sales profession, by suggesting that future sales growth and B2B sales success requires businesses to invest not just in digital assets, but also in building a great sales force.

Utilising machines to automate key activities such as information gathering, research on buying behaviours and trends, due diligence, and answering customer questions in real time, leaves sellers free to undertake more strategic decision making and human-touch relationship building tasks with an even greater level of clarity. No touch point left unturned, no opportunity missed. This is particularly important when targeting first-time customers.

According to the report these customers are more likely to be looking for direct interaction with sales teams, and the fastest-growing companies are utilising tools to address customer needs at each stage of their purchase journey and, even better, to anticipate enquiries and offer lightning-fast responses and recommendations.

The most successful sellers today are those that capitalise on every business moment in a way that is customer-centric, contextually aware, empathetic and personalised. Today’s buyers are turned off by generic mass broadcast communications, spamming and untargeted, untimely, irrelevant and poorly-delivered engagements.

Predictive analytics furnishes sellers with rich customer data and machine learning algorithms remove the guess work when it comes to relevance and timing, ensuring sellers know the best time to act and the most appropriate attention-grabbing ways to engage with customers and prospects.

My takeaway here is to invest in your sales force by investing in tools that make their lives easier, leaving them free to immerse themselves in the most creative, rewarding and engaging aspects of their roles, and augment their own abilities. In a recent article by our Co-Founder and CTO Steve Borthwick, he talks about employing AI co-workers.

When machine joins the team, everything will get easier – AI co-workers will reduce the likelihood that sellers miss a valuable business moment or engagement opportunity, fail to respond to a customer need or respond in the wrong way, or fail to spot a market trend that could open new doors. Importantly they will always engage with the customer in the way they want to engage.

Make better decision faster – the science of predicting customer needs

The McKinsey report states that in the next five years the fastest-growing companies will be using AI sales software incorporating advanced analytics and machine learning to address fundamental strategic issues, such as what sales opportunities to pursue, what resources to allocate to which accounts, and what behaviours to prioritize in order to drive sales productivity.

The authors state that the days when lead generation relied entirely on local field knowledge are fading fast, and instead market leaders of the future will use advanced analytics to build granular account profiles augmented with relevant external data such as news reports, public financial information, and social media to generate a truly 360-degree view of each customer.

This immediately struck a chord – this is a message we have been talked about for years. We believe there are four key ways AI will enable sellers to make better decisions faster:

1. Prediction
Machine learning will enable businesses to construct predictive models based on patterns of event types and customer attributes, that correlate more or less with eventual success. When sellers know exactly what the next steps are, they can better predict success and avoid failure, resulting in more sophisticated sales strategies, campaigns, and product or service development. As time goes by and the volume of data improves precision and predictive capacity, these models will advance, enabling faster and more accurate predictions of customer needs, pain, market challenges and opportunities – before customers themselves even realise what lies ahead.

2. Augmentation
Advances in the performance and accuracy of AI sales software will present many new opportunities to augment real-world lead generation activities with virtual sophistication. It will help to navigate the big-data swamp by automatically locating the most relevant content, then ranking and triaging it based on where that particular customer is in the sales cycle, as well as the individual motivations of people involved.

3. Active Segmentation
AI models will seamlessly augment static, cold data with real-time insights and real-world events, ensuring that firmographic data is bang up to date and helping to uncover previously missed opportunities and new revenue streams. By using AI to gain an understanding of experiential factors based on the news, views and opinions of the prospect or customer will deliver a valuable 360-degree view of their ecosystem. The result is a much more targeted and accurate set of measures and triggers that can be used to perfect segmentation, lead generation and execution.

4. Active Engagement
A shift from business applications that simply record the qualitative and quantitative facts of a sales engagement, to AI-grounded applications that constantly analyse action or inaction will mark a huge advance in engagement capability over the coming years. AI and machine learning techniques correlating patterns of sharing with customers and prospects with actual open rates will predict how likely it is an individual will be interested in receiving content, then automatically sharing it with the most relevant prospects, partners and customers to become a pivotal part of the sales process – maintaining a touch point with the client and ensuring a level of attentiveness across an entire portfolio of people and businesses that would be very difficult to do manually.

My key takeaway? It used to be said that the best sales people are the best predictors, with sellers relying on gut instinct to identify behaviours that drive sales productivity and make account coverage decisions. But prediction is no longer an art form, it’s a science – and the winners will be those that invest in exploiting artificial intelligence for sales, (predictive analytics, machine learning and natural language processing) to improve their decision making, B2B sales techniques and interaction with the customer.

Turn rookies into rainmakers – the science of hiring and developing top sales talent

The McKinsey report states a lot about the importance of hiring the right talent, and investing significant time and resources toward nurturing and growing that talent.

I was surprised to read that many companies don’t feel they’re equipped with the right sales talent to bring them into the future (this was especially prevalent among slow growers), but not quite so surprised at the finding that 48% of fast-growth companies indicated they invest significant time and resources in sales training, compared to just 22 percent of slow-growth companies.

Mckinsey Sales Growth Survey

Building a top sales team is not an art form, it’s a science in that you must take a strategic approach in terms of hiring and developing star performers.

For my takeaway therefore, I turn to the wisdom of our CEO Andrew Yates, and his recent whitepaper entitled Lessons from an entrepreneur – How to invert the 80:20 rule and boost sales team success.

Here are five sure-fire approaches to turn rookies into rainmakers:

1. Processes that help, not hinder – there’s a lot to track: sales process, forecasting, training, technology, hiring – but you don’t want these process documents to be a thick rulebook. Great sales people enjoy a bit of freedom, so process documents should be useful guidance to train staff, track performance and increase sales, not an intimidating and confining rulebook. This is far too limiting for really great sales people. They need the flexibility to approach prospects in their own way, with their own style, and to run their accounts like their own business. It’s what makes great sales people great!

2. Build a pipeline of talented people – waiting until you need to hire someone new is leaving it too late. To get the best sales people you need to know who they are, which areas they are specialists in, and what they are up to – long before there is an actual need for new staff. The best way to accomplish this is to create a detailed database of prospective employees, just as you might do for potential clients, and track what these star sellers are up to in order to create a pipeline of talented staff to join your team

3. Don’t skimp on the training – surprisingly, only 66% of companies actually train their new employees. Likewise around 60% of businesses at any one time are planning to introduce new technology into the workplace that would require staff training. If no training is provided, employees will be wasting valuable time getting to grips with the valuable tools a business has invested in, damaging return on that investment. Good training, on the other hand, cuts down on wasted time trying to figure things out, minimises easily avoidable mistakes and instils your new team members with the confidence to go out engage and make sales

4. Give meaning to their work – people and companies can be inspiring, but what really drives great sales is the ‘why’ behind the business. Indeed 71% of millennials believe that meaningful work is an essential factor in defining career success. I have no doubt that the same is true even of the most seasoned and established sales professional. It’s the ’why’ that provides a reason for getting out of bed in the morning and gives your salespeople the focus they need to achieve fantastic results. Today’s sellers crave more than “just a job.” They want meaningful work that gives them purpose and inspires them to give it their all. Inspiration is the spark that lights the fire – it’s what gets your team going.

5. Accurately incentivise – providing the right incentives to the right people is essential. Invest in their development and reward them based on contribution and drive, not on age or time served. The Zuckerberg philosophy of “You can do anything here if you can prove it” is certainly a great standard to work by. If you can integrate your performance tracking tools with your compensation system you can ensure that people are accurately rewarded for their achievement.

I found the McKinsey report to be a fascinating read. My final takeaway is that the future of B2B sales growth is about investing in experimenting – pushing the boundaries, just as those pioneers of science, engineering and medicine do.

Put the old ways of the past behind you and instead invest in the future of sales teams (and the future of the sales profession) and sales success by adapting to changes, investing in technology and developing sales behaviours – the science of B2B sales.