Why tech-enabled go-to-market innovation is critical for industrial companies—and what to do about it

Why tech-enabled go-to-market innovation is critical for industrial companies—and what to do about it

Why tech-enabled go-to-market innovation is critical for industrial companies—and what to do about it

Companies that overhaul their go-to-market strategy with savvy use of technology improve their revenue growth and customer satisfaction.

Industrial companies face a compelling opportunity to innovate their traditional go-to-market channels and models. The simultaneous rise of digital commerce, powerful digital players, and millennials as the dominant customer segment is disrupting the whole sector and changing the way in which industrial companies need to go to market (see sidebar, “Disruption by numbers”).

Yet few of them are managing to adapt quickly enough. Over the last five years, McKinsey has measured the Digital Quotient (DQ) of approximately 200 B2C and B2B companies around the world by evaluating 18 management practices related to digital strategy, capabilities, culture, and organization that correlate most strongly with growth and profitability.

The study shows that B2B companies trail consumer companies in terms of their overall digital maturity: the average DQ score for the 47 B2B companies in our study was 28, compared with 35 for consumer companies (Exhibit 1).

Value drivers in tech-enabled selling

While most industrial companies have come to terms with the need to make more strategic use of technology,1 they are often unsure of how to proceed or are focused on the wrong initiatives, resulting in halting action and a failure to build significant value. On the other hand, those companies that move quickly and decisively to transform their go-to-market channels, models, and culture through technology should be able to unlock substantial value: top quartile B2B players generate 3.5 percent more revenue and are 15 percent more profitable than the rest of the B2B field.

Where the value lies

Our detailed analysis has identified a pool of $74 billion to $298 billion in revenue growth that could be tapped through enabling technology in sales (Exhibit 2). The value comes primarily through new customer experiences, refined pricing, and enhanced selling processes.

$74 billion to $298 billion of revenue growth can be delivered across industrials through innovative approaches to selling.

An innovative approach to selling

Our experience in working with dozens of industrial companies has helped to identify where the main source of value is across the four main steps of the selling process: the presales stage, the sales process, the transaction itself, and IoT-enabled selling (Exhibit 3).

Value drivers in tech-enabled selling

Enhancing presales and discovery through digital marketing

Presales covers all customer interactions that lead to the discovery of the brand, product, or service. Industrial companies frequently underestimate the impact of a poor presales experience, such as suboptimal websites or over-reliance on traditional channels for lead generation.

However, as the customer landscape shifts toward digital channels, and as e-commerce matures, companies need to develop consumer-centric strategies that will drive traffic to their web pages and improve lead generation. Doing so significantly increases performance, as McKinsey analysis shows that companies with strong presales capabilities consistently achieve win rates of 40 to 50 percent in new business and 80 to 90 percent in renewal business, well above the average.

We typically observe four practices that work best: implementing agile digital marketing, optimizing paid search (SEM), maximizing organic search (SEO), and personalizing next-product-to-buy algorithms. These areas often require adopting digital technologies such as advanced analytics and artificial intelligence, and optimizing marketing across traditional and digital channels.

An auto retail company set up an agile digital-marketing war room to manage and analyze effectiveness of all campaigns on a daily basis. As a result, the client learned that paid search (search-engine marketing), organic search (search-engine optimization), and email marketing were most effective in attracting profitable customers. By shifting spend to those digital channels, the company saw improvements in traffic (25 to 35 percent) and conversion (greater than 25 percent) within ten weeks.

Another industrial company developed detailed customer profiles by aggregating multiple data sources such as customer-profile loyalty identifications and historical sales. From this input, a predictive analytical model was created to show sales patterns based on customer purchasing behavior and provide recommendations on next product to buy. By sending personalized emails and product recommendations, the company was able to increase email conversion by 30 to 40 percent. This approach also helped identify effective selling processes and profitable customer profiles for future sales.

Transforming customer experience

A profitable sales process relies on developing a deeper understanding of how customers are behaving at each step in their decision journey.

This helps companies understand at a granular level where customer pain points and opportunities are and then to establish clear priorities for developing digital tools to improve sales productivity and better engage with customers. Levers typically used include digital buying/fulfillment, optimized sales-coverage models, and customer decision journeys.

For example, a large equipment manufacturer conducted customer decision journey (CDJ) research, interviewing and surveying end customers to understand the biggest pain points in their journeys (Exhibit 4).

Breaking down key pain points in the customer decision journey

Many industrial companies miss this step, putting them at risk of investing in digital tools that don’t meet genuine customer needs. One company discovered that customers spent a significant amount of time understanding product specifications and matching them to their requirements during the quote stage. That led to them starting quotation requests for products that were not optimized for their needs.

Insights like these allowed the organization to focus its energies, leading to the development of a minimum viable product prototype with a well-defined feature set to address prioritized pain points. One example was the creation of a web tool that allowed end customers to browse and compare products by specs, a core customer need.This approach and rapid iteration reduced the time needed to develop a full solution from three years to nine months, and the prototype development phase from nine months to six weeks. By creating improved experiences, we estimate that it is possible to increase customer engagement and conversion by 30 to 40 percent.

In another company, CDJ analysis revealed two major customer pain points. One, customers were having difficulties in comparing and getting quotes for products. Two, it was cumbersome for customers to track and monitor open orders, because all processes had to be done manually and required multiple interactions between customers and sales reps.

Based on these findings, sales leaders developed a web-based platform prototype to allow customers to research products, build their bill of materials (BOM) and receive an initial quote with minimal sales support. Additionally, the platform allowed sales reps and customers to collaborate on requests, share the status of orders, and exchange proactive notifications of any changes. Finally, on the back end, the platform allowed sales reps to have full visibility of the accounts, view open invoices, and flag potential delays or anticipated issues. The implementation of the platform generated significant improvement of customer experience and increased sales productivity by 10 to 15 percent.

Based on our experience, technology solutions based on CDJ analysis typically lead to a 3 to 5 percent increase in revenues and increased customer engagement and loyalty to the brand.

Optimizing pricing

The development of digital and analytical tools in transactions, such as dynamic deal-scoring models and data-driven performance management, has significant benefits: our experience suggests significantly improved operating income, optimized B2B product pricing to specific customer segments, maximized value capture in each transaction, and end-to-end pricing-process management throughout the lifetime of products and contracts.

Improving price capabilities is also critical given how rapidly e-commerce players can adjust prices and capture opportunities. It is not uncommon for eCommerce players to use dynamic pricing algorithms for individual stock-keeping units (SKUs) on a daily basis. Although such algorithms might be harder to apply in a B2B setting due to constraints on data collection and frequency of transactions, they offer a vision of what is possible as B2B companies’ digital and analytical capabilities mature.

One impressive source of value comes from reducing unexplained variability in discounting. A dynamic deal-scoring tool can provide objective guidance for sales reps at the time of deal making. Analyses at a large wholesale distributor, for example, showed that several similar customers received significantly different levels of rebates and discounts due to circumstantial factors, such as sales rep underperformance or unjustified customer requests.

To address this issue, a dynamic deal-scoring model was developed using historical data, relevant parameters, and advanced analytical techniques to provide an assessment of expected profitability for each incoming deal (Exhibit 5). The tool delivered results to the sales rep during the quotation phase of the process through an app. Empowered by this information, sales reps clearly understood the performance potential of each incoming deal request and could make a real-time assessment of which levers, such as payment terms or add-on services, could be used to improve deal performance and provide better value for customers.

Steps to implement a dynamic deal-sourcing solution

The implementation of a dynamic deal-scoring solution significantly improved gross profits (1 to 3 percent) through more targeted discounting and effective use of rebates, and reduced the quoting process from months to a week, creating a much better buying experience for customers and potentially improving win-rates.

Industrial companies also have the opportunity to use analytical tools to dynamically set prices at scale and continuously improve pricing performance to drive business objectives. The potential impact can be significant, typically a 2 to 7 percent return on sales in value to the bottom line. However, because sales leaders in industrial companies tend to approach each deal as a unique one, they have been slow to implement advanced analytical techniques to unlock pricing opportunities.

(Technology has a significant role to play in the postsales process as well. For more on that, please read “How disruptive technologies are opening up innovative opportunities in services” in this collection).

Enabling IoT at dealers and retailers

Original equipment manufacturers (OEMs) and consumer packaged goods companies (CPGs) have started to work with dealer and channel partners to use technology more effectively in sales. IoT-enabled innovations are an area with great potential.

Typically, IoT-enabled innovations can unlock value by improving real-time traffic measurement, curbside pickup, intelligent in-store navigation and promotions, and inventory management. To better understand the potential, we reviewed automation opportunities across ten major work-flow activities in retail, including shelving and replacement, pricing and promotion, and checkouts, and identified six major use cases where technology and algorithms can be deployed to increase store performance.

One opportunity identified by our research was combining sensors with smartphone technologies such as Bluetooth to map customers’ positioning within the store and then provide tailored offers and information to increase the propensity to buy.

Another possible opportunity was to develop a fully automated, nonstop checkout, using a combination of video-surveillance technology and machine-learning algorithms to accurately charge customers >99.9 percent of the time. Another interesting use case developed was to leverage radio-frequency ID (RFID) tags, whose price has declined significantly in recent years, to automate the inventory monitoring process, freeing up store staff to focus on customer-facing activities.

Our analysis shows that the total value generated by these improvements can be significant, with estimated increases in revenue of 3 to 10 percent, reductions in operating costs of 15 to 25 percent, and a 5 to 10 percent increase on average in operating profit.

At a dealer network, a system of sensors was installed to reliably capture store traffic. The data generated was analyzed through advanced analytics to directly measure several indicators, such as store performance, marketing ROI, effect of store initiatives, and the effect of weather, among others. With this analysis in hand, the team identified several initiatives to improve performance and maximize return on investment by eliminating underperforming marketing campaigns, for example, or refocusing promotions. Furthermore, there was an opportunity to adapt the system to enable the detection of loyalty customers, and create targeted and tailored experiences for them such as matching them with the most experienced staff.

Getting started

No two industrial companies face the same opportunities and challenges in enabling sales through technology, but all companies need to tackle a few key things:

Invest in understanding your customer at a granular level. Begin by understanding the areas most in need of improvement along your customer decision journeys. This requires getting closer to your customers and understanding the channels they use to research and buy, research through advanced analysis as well as close observation. This process is best when it is continuous and based on frequent communications through dedicated channels between sales and product-development teams.

Construct one source of truth for your selling data. To fully capture the revenue uplift from selling, it is critical to combine transactional data across channels and systems into a single data lake. This establishes a single source of insight for your sales and tech teams. This may sound trivial, but it’s often the hardest thing to accomplish, given the multiplicity of data sources in many companies.

Define a big opportunity. With insights into customer buying behaviors in hand, the best companies go for big opportunities. These are comprehensive across a range of levers including churn reduction, incremental sales from enhancing the share of wallet, pricing opportunities, and sales from new channels such as e-commerce.

Link your technology roadmap to identified value. Your technology investments should be in lockstep with the opportunity you’re going after. For example, if there are significant shifts to e-commerce in certain kinds of transactions, then establishing the right corresponding channel and right presales infrastructure is critical to capturing that opportunity. Similarly, if the variations in pricing practices are significant for similar transactions, then it is critical to invest in dynamic deal-scoring tools. The roadmap should focus on near-term horizons (one to two years) given constantly evolving innovations and customer needs.

Deploy the technology so you can be responsive. You should deploy solutions using agile methods so that you can rapidly respond to sales and customer feedback. The traditional waterfall approach often results in lost momentum and in a solution that is not in tune with customer needs.

Invest in a “transformation structure.” Your technology investments need to be tracked and managed as a major change initiative. Sales and customer training is critical to ensure adoption. Granularity in performance management linking the investment to expected results helps to ensure the value is being captured, and allows the business to adjust quickly if necessary.


Technology isn’t a panacea for digital transformations in sales. It is a core component of a holistic change program that requires effective and deliberate management. But sales organizations that find that balance can deliver massive value to their businesses.

About the author(s)

Venkat Atluri is a senior partner in McKinsey’s Chicago office, where Satya Rao is a partner and Andrew J. Wong is a consultant.

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