Driven by digitalized operating models, B2B sales have seen sweeping changes over the recent period amid rising customer demand for more seamless and transparent services.1 However, many industrial companies are failing to keep pace with their more commercially focused peers and, as a result, are becoming less competitive in terms of performance and customer services.
The most successful B2B players employ five key tactics to sharpen their sales capabilities: omnichannel sales teams; advanced sales technology and automation; data analytics and hyperpersonalization; tailored strategies on third-party marketplaces; and e-commerce excellence across the full marketing and sales funnel.2
Companies using all of these tactics are twice as likely to see more than 10 percent market share growth than companies focusing on just one.3 However, implementation is not as simple, requiring a strategic vision, a full commitment, and the right capabilities to drive change throughout the organization. Various leading European industrial companies—part of McKinsey’s Industrial Gamechangers on Go-to-Market disruption in Europe—have achieved success by implementing the first three of these five sales tactics.
Omnichannel sales teams
The clearest rationale for accelerating the transition to omnichannel go-to-market is that industry players demand it. In 2017, only about 20 percent of industrial companies said they preferred digital interactions and purchases.4 Currently, that proportion is around 67 percent. In 2016, B2B companies had an average of five distinct channels; by 2021, that figure had risen to ten (Exhibit 1).
Excelling in omnichannel means enabling customers to move easily between channels without losing context or needing to repeat information. Companies that achieve these service levels report increased customer satisfaction and loyalty, faster growth rates, lower costs, and easier tracking and analysis of customer data. Across most of these metrics, the contrast with analogue approaches is striking. For example, B2B companies that successfully embed omnichannel show EBIT growth of 13.5 percent, compared to the 1.8 percent achieved by less digitally enabled peers. Next to purely digital channels, inside sales and hybrid sales are the most important channels to deliver an omnichannel experience.
Differentiating inside versus hybrid sales
Best-in-class B2B sellers have achieved up to 20 percent revenue gains by redefining go-to-market through inside and hybrid sales. The inside sales model cannot be defined as customer service, nor is it a call center or a sales support role—rather, it is a customer facing, quota bearing, remote sales function. It relies on qualified account managers and leverages data analytics and digital solutions to optimize sales strategy and outreach through a range of channels (Exhibit 2).
The adoption of inside sales is often an advantageous move, especially in terms of productivity. In fact, inside sales reps can typically cover four times the prospects at 50 percent of the cost of a traditional field rep, allowing the team to serve many customers without sacrificing quality of service.5 Top performing B2B companies are 50 percent more likely to leverage inside sales.
Up to 80 percent of a company’s accounts—often smaller and medium-sized customers, accounting for about half of revenues—can be covered by inside sales teams.6 The remaining 20 percent often require in-person interactions, triggering the need for hybrid sales. This pertains to highly attractive leads as well.
Hybrid sales is an innovative model combining inside sales with traditional in-person interactions. Some 85 percent of companies expect hybrid sales will be the most common job role within three years.7 Hybrid is often optimal for bigger accounts, as it is flexible in utilizing a combination of channels, serving customers where they prefer to buy. It is scalable, thanks to the use of remote and online sales, and it is effective because of the multiplier effect of numerous potential interactions. Of companies that grew more than 10 percent in 2022, 57 percent had adopted a hybrid sales model.8
How an industrial automation solution player implemented game-changing inside sales
In 2019, amid soaring digital demand, a global leader in industrial digital and automation solutions saw an opportunity to deliver a cutting-edge approach to sales engagement.
As a starting point, the company took time to clearly define the focus and role of the inside sales team, based on product range, customer needs, and touchpoints. For simple products, where limited customer interaction was required, inside sales was the preferred go-to-market model. For more complex products that still did not require many physical touchpoints, the company paired inside sales teams with technical sales people, and the inside sales group supported fields reps. Where product complexity was high and customers preferred many touch points, the inside sales team adopted an orchestration role, bringing technical functions and field sales together (Exhibit 3).
The company laid the foundations in four key areas. First, it took time to sketch out the model, as well as to set targets and ensure the team was on board. As in any change program, there was some early resistance. The antidote was to hire external talent to help shape the program and highlight the benefits. To foster buy-in, the company also spent time creating visualizations. Once the team was up and running, early signs of success created a snowball effect, fostering enthusiasm among both inside sales teams and field reps.
Second, the company adopted a mantra: inside sales should not—and could not—be cost saving from day one. Instead, a significant part of the budget was allocated to build a tech stack and implement the tools to manage client relationships. One of the company’s leaders said, “As inside sales is all about using tech to obtain better outcomes, this was a vital step.”
The third foundational element was talent. The company realized that inside sales is not easy and is not for everyone—so finding the right people was imperative. As a result, it put in place a career development plan and recognized that many inside sales reps would see the job as a stepping stone in their careers. Demonstrating this understanding provided a great source of motivation for employees.
Finally, finding the right mix of incentives was key. The company chose a system based on compensation and KPI leading and lagging indicators. Individual incentives were a function of whether individuals were more involved with closing deals or supporting others, so a mix of KPIs was employed. The result was a more motivated salesforce and productive cooperation across the organization.
Advanced sales technology and automation
Automation is a key area of advanced sales technology, as it is critical to optimizing non-value adding activities that currently account for about two-thirds of sales teams’ time. More than 30 percent of sales tasks and processes are estimated to be partially automatable, from sales planning through lead management, quotation, order management, and post-sales activities. Indeed, automation leaders not only boost revenues and reduce cost to serve—both by as much as 20 percent—but also foster customer and employee satisfaction. (Exhibit 4). Not surprisingly, nine out of ten industrial companies have embarked on go-to-market automation journeys. Still, only a third say the effort has achieved the anticipated impact.9
Leading companies have shown that effective automation focuses on four areas:
- Lead management: Advanced analytics helps teams prioritize leads, while AI-powered chatbots contact prospective customers via text or email and schedule follow-up calls at promising times—for example, at the beginning or end of the working day.
- Contract drafting: AI tools automate responses to request for proposal (RFP) inquiries, based on a predefined content set.
- Invoice generation: Companies use robotic process automation to process and generate invoices, as well as update databases.
- Sales commission planning: Machine learning algorithms provide structural support, for example, to optimize sales commission forecasting, leading up to a 50 percent decline in time spent on compensation planning.
How GEA seized the automation opportunity
GEA is one of the world’s most advanced suppliers of processing machinery for food, beverages, and pharmaceuticals. To provide customers with tailored quotes and services, the company launched a dedicated configure, price, quote (CPQ) system. The aim of the system was to enable automated quote creation that would free up frontline sales teams to operate independently from their back office colleagues. This, in turn, would boost customer interaction and take customer care to the next level.
The work began with a bottom-up review of the company’s configuration protocols, ensuring there was sufficient standardization for the new system to operate effectively. GEA also needed to ensure price consistency—especially important during the recent supply chain volatility. For quotations, the right template with the correct conditions and legal terms needed to be created, a change that eventually allowed the company to cut its quotation times by about 50 percent, as well as boost cross-selling activities.
The company combined the tools with a guided selling approach, in which sales teams focused on the customers’ goals. The teams then leveraged the tools to find the most appropriate product and pricing, leading to a quote that could be enhanced with add-ons, such as service agreements or digital offerings. Once the quote was sent and agreed upon, the data automatically would be transferred from customer relationship management to enterprise resource planning to create the order. In this way, duplication was completely eliminated. The company found that the sales teams welcomed the new approach, as it reduced the time to quote (Exhibit 5).
Data analytics and hyperpersonalization
Data are vital enablers of any go-to-market transformation, informing KPIs and decision making across operations and the customer journey. Key application areas include:
- lead acquisition, including identification and prioritization
- share of wallet development, including upselling and cross-selling, assortment optimization, and microsegmentation
- pricing optimization, including market driven and tailored pricing, deal scoring, and contract optimization
- churn prediction and prevention
- sales effectiveness, so that sales rep time allocations (both in-person and virtual) are optimized, while training time is reduced
How Hilti uses machine data to drive sales
Hilti is a globally leading provider of power tools, services, and software to the construction industry. The company wanted to understand its customers better and forge closer relationships with them. Its Nuron battery platform, which harvests usage data from tools to transform the customer experience and create customer-specific insights, provided the solution.
One in three of Hilti’s frontline staff is in daily contact with the company’s customers, offering advice and support to ensure the best and most efficient use of equipment. The company broke new ground with its intelligent battery charging platform. As tool batteries are recharged, they transfer data to the platform and then to the Hilti cloud, where the data are analyzed to produce actionable insights on usage, pricing, add-ons, consumables, and maintenance. The system will be able to analyze at least 58 million data points every day.
Armed with this type of data, Hilti provides customers with advanced services, offering unique insights so that companies can optimize their tool parks, ensuring that the best tools are available and redundant tools are returned. In the meantime, sales teams use the same information to create deep insights—for example, suggesting that companies rent rather than buy tools, change the composition of tool parks, or upgrade.
To achieve its analytics-based approach, Hilti went on a multiyear journey, moving from unstructured analysis to a fully digitized approach. Still, one of the biggest learnings from its experience was that analytics tools are most effective when backed by human interactions on job sites. The last mile, comprising customer behavior, cannot be second guessed (Exhibit 6).
In the background, the company worked hard to put the right foundations in place. That meant cleaning its data (for example, at the start there were 370 different ways of measuring “run time”) and ensuring that measures were standardized. It developed the ability to understand which use cases were most important to customers, realizing that it was better to focus on a few impactful ones and thus create a convincing offering that was simple to use and effective.
A key element of the rollout was to ensure that employees received sufficient training— which often meant weeks of engagement, rather than just a few hours. The work paid off, with account managers now routinely supported by insights that enrich their interactions with customers. Again, optimization was key, ensuring the information they had at their fingertips was truly useful.
Levers for a successful transformation
The three company examples highlighted here illustrate how embracing omnichannel, sales technology, and data analytics create market leading B2B sales operations. However, the success of any initiative will be contingent on managing change. Our experience in working with leading industrial companies shows that the most successful digital sales and analytics transformations are built on three elements:
- Strategy: As a first step, companies develop strategies starting from deep customer insights. With these, they can better understand their customers’ problems and identify what customers truly value. Advanced analytics can support the process, informing insights around factors such as propensity to buy and churn. These can enrich the company’s understanding of how it wants its go-to-market model to evolve.
- Tailored solutions: Customers appreciate offerings tailored to their needs.10 This starts with offerings and services, extends to pricing structures and schemes, and ways of serving and servicing. For example, dynamic pricing engines that model willingness to pay (by segment, type of deal, and route to market) may better meet the exact customer demand, while serving a customer completely remotely might better suit their interaction needs, and not contacting them too frequently might prevent churn more than frequent outreaches. Analytics on data gained across all channels serves to uncover these needs and become hyperpersonalized.
- Single source of truth: Best-in-class data and analytics capabilities leverage a variety of internal and external data types and sources (transaction data, customer data, product data, and external data) and technical approaches. To ensure a consistent output, companies can establish a central data repository as a “single source of truth.” This can facilitate easy access to multiple users and systems, thereby boosting efficiency and collaboration. A central repository also supports easier backup, as well as data management and maintenance. The chances of data errors are reduced and security is tightened.
Many companies think they need perfect data to get started. However, to make productive progress, a use case based approach is needed. That means selecting the most promising use cases and then scaling data across those cases through speedy testing.
And with talent, leading companies start with small but highly skilled analytics teams, rather than amassing talent too early—this can allow them to create an agile culture of continual improvement and cost efficiency.
As shown by the three companies discussed in this article, most successful B2B players employ various strategies to sharpen their sales capabilities, including omnichannel sales teams; advanced sales technology and automation; and data analytics and hyperpersonalization. A strategic vision, a full commitment, and the right capabilities can help B2B companies deploy these strategies successfully.
