9 Requirements for Effective Cross-Selling in High Tech

by Mike Kelleher

The impact of digital transformation on the Technology sector is staggering. Billion-dollar technology incumbents, hyper-growth emerging stars, and new start-ups alike are not only developing and supplying the catalysts of digital transformation to their customers across all industries, but they also face the need to adapt themselves to continually accelerate revenue growth.

Emerging trends like AI-powered insights, IoT and Intelligent Edge, and even Blockchain will certainly change the operating models for many firms and impact the competitive dynamics of the industry for years to come. In the short-term, they are presenting opportunities for how traditional tech firms acquire, grow and retain customers. This is especially true in the area of cross-selling or expanding share-of-wallet through increased usage across a tech firm’s entire product portfolio. If traditional firms aren’t accurately anticipating the needs of their customers or understanding their defection risk, they are exposed to disintermediation by new entrants or competitors who do.

Cross-selling is the fastest, most profitable path to incremental revenue growth, period. Assuming a firm has a 30% wallet share within an account, attaining just 5% more in account share grows account revenues by 17%. And with the cost of customer acquisition as high as 25X more expensive than customer penetration, the economics of cross-selling are very compelling. Recognizing this, cross-selling has become a strategic priority for most tech firms – yet many firms still appear to be far from realizing its potential or executing against it with scalable efficiency.

Why is this?  For some, it may be the challenges associated with overcoming organizational complexity resulting from multiple Lines of Business, diverse functional areas and different business processes that must be coordinated to deliver effective cross-sell programs.

It may also be the fact that cross-selling responsibility is often left to the “last mile” (the last touch in the buying journey) in that Account Execs or channel partners often simply don’t have the time, skills, or incentives to effectively implement programs at scale.  Or, efforts are driven by product owners who take a product-centric view of expanding licenses or hardware purchase as opposed to the customer-centric view of product portfolio penetration.

Here is our list of nine requirements for building effective and scalable cross-selling programs:

1) Be customer-centric.

Too many cross-sell programs are still organized around lines of business and driven by a product- centric view of increased consumption within the same product family. Effective cross-sellers build a customer-centric view of opportunity and take a longer-term view of customer value. The most effective cross-sell efforts are led by segment marketers who have responsibility for specific customer segments, working with the product marketing teams and sales channels to coordinate on execution.


2) Establish a single view of the customer.

Many firms still have a difficult time building a unified view of the overall customer relationship. This includes all product usage and transactional history, service and support history, etc., as well as identifying and integrating external data sources that provide additional insights into buyer behavior and attitudes.

Identifying patterns of behavior across products is essential for understanding and anticipating customer needs. In turn, it informs segmentation and personas in #3 below.

But don’t wait for the completion of an expensive, multi-year data warehouse project. Agile firms today are taking advantage of low-cost storage, data lake architectures, and data connectors to quickly build data repositories. These allows data science teams quick access for specific use cases without processing overhead associated with large inflexible data warehouses.

For more information on the Promise of the Marketing Data Platform, Click Here


3) Build actionable buyer segments and personas.

Utilize data from # 2 – supplemented with primary research – to build actionable segmentation and personas. These will allow you to personalize your interactions with existing customers in ways they have come to expect; based on the entirety of their relationship with you and reflecting an understanding of their needs.  Append and maintain persona assignments within your customer database to ensure your segmentation is actionable.

For more information on Creating Actionable Segmentations and Personas, Click Here


4) Create a scalable analytical engine targeted to specific, prioritized use cases
.

Account expansion, customer share-of-wallet growth, product usage extension —all of these strategic goals beg the same question; how do I get a given customer to buy more, use more, or buy something new?

Use an agile, reproducible approach to develop and manage a library of predictive cross-selling models.  Cross-sell models use data about the current installed base and compare this with data on other accounts where you have successfully realized portfolio share-of-wallet growth.

Consider buyer segmentation, RFM, CLV, next logical product, attrition risk and retention, and marketing mix optimization, among other models while deploying a disciplined approach to managing your data science operations and ensuring reproducibility, scalability, and accountability.

For more information on Creating a Product-Centric Data Science Organization, Click Here


5) Listen to your customers, stalk your competition, foresee your disruptors.

Robust cross-sell programs require a deep understanding of your accounts. This includes how they perceive your solutions, what competitors are selling into those accounts and what new start-up and hyper-growth disruptors are emerging.

Best-in-class firms leverage “always-on” market intelligence capabilities. Those that track customer feedback, channel partners’ vendor preferences, competitive movements, and emerging disruptors are best prepared to make needed changes to their customer messaging and executive on time-sensitive sales outreach. This intelligence is best fed back to product- and customer-segment marketing teams and sales channels (field, inside, channel) for Account-Based Marketing activities and sales enablement programs.


6) Create content aligned with personas and buyer’s journey.

Today’s customers engage with your organization via multiple channels. With 24/7 availability of your content and resources, it can be challenging to provide a consistent experience across every channel (especially direct versus partner). Think of a potential buyer researching new AI-enabled Analytics or IoT/Edge Computing solutions for 2H 2019. This buyer can easily research opportunities online, get side-by-side comparisons from third-party thought leaders, chat online or over the phone with category experts, and then set up an appointment with a channel for a face-to-face deep-dive discussion.

If the user experience across all these channels isn’t integrated – and customers receive different responses across different channels from the same company – the likelihood of successfully cross-selling those customers goes down considerably. Utilizing a consistent framework and taxonomy to map required content to the buyer’s journey is critical to ensure a consistent, personalized and relevant experience regardless of product, channel or stage in the journey.

For more information on Creating a Consistent Customer Experience, Click Here


7) Implement a disciplined cross-channel contact strategy and cadence.

Disciplined cross-sellers implement and adhere to well-structured contact strategies that are based on analytics and insight (i.e., using the scores developed in #4 above). These strategies help determine what that cadence should be, which channel should engage buyers and influencers, and what the product/solution and message should be.

This requires close coordination between marketing and sales. One of the most successful cross-sell programs we have ever seen actually rescored their entire customer population each week. They did so by using updated transactional and market response data, and then prescribing a set of dynamic business rules to determine where the opportunities were to be routed the following week. A well-defined nurture stream for the next logical product was presented or the prospect was routed to a sales agent.

In either event, the contact strategy and cadence were well-defined for each product and each step in the buyer’s journey. Content and messaging for each segment were defined and utilized as “fuel” for each outreach and delivered into the marketing automation tools and the CRM (See #8 below). The business rules were dynamic and could be modified weekly based on underlying business conditions. This forced an interlock each week between sales and marketing and helped develop shared accountability for results.

To view the Tech contact strategy case study, Click Here


8) Insert insights and content into workflow tools.

The best insights and AI are useless unless they can be easily understood and acted upon by your sales and marketing channels. Delivering predictive analytics, relevant content and personalized messaging into existing customer contact workflow platforms is critical for successful cross-selling at scale. We have found that loosely coupled architectures are dramatically better over the long run than tight integrations with CRM or MarTech platforms.

Most companies are using multiple platforms to manage the end-to-end customer journey. The need to insert insight into each one of these platforms—and to gather feedback from the customer interaction directed by those platforms. This is critical to managing the process holistically and understanding where the customer is in the process at any given point in time.

Rather than working to integrate multiple systems, the better alternative is to deliver analytics and content via a set of standardized endpoints that any CRM or MarTech platform can use. When that next great piece of technology is rolled out—or when an incumbent like Salesforce raises its prices by 20%— it’s no problem. It just requires updates to an adaptor layer versus. tearing out a bunch of proprietary APEX code from Salesforce and trying to remember what the developer was thinking.

Fortunately, all CRM and marketing automation systems—including Salesforce—share the same basic architecture. The objects Account, Contact, Lead, Opportunity, Product, etc. don’t really vary, and haven’t for 25 years.

Cross-selling recommendations also share the same DNA. Typically, the API calls for cross-selling include several microservices that, when taken together, form the basis of the contact and content strategy outlined in #7 woven into the CRM / Martech stack.

For insights on the Microsoft-SAP-Adobe Open Data Alliance, Click Here


9) Relentlessly test, measure and track.

Finally, any successful cross-sell program – in fact, any sales and marketing program – requires a relentless focus on test and learn, agile pilots, on-going measurement and optimization from start to finish.

This process starts with establishing a pro forma ROI when any new cross-sell model is slated for development. Writing down what you are trying to accomplish, and estimating how its effectiveness will be measured, puts the entire team on much better footing for success. This should be done before a single data query is executed.

To learn more about Measuring Return on Analytics, Click Here

Implementing agile pilots using test and learn methods such as A/B testing can quickly deliver insight into optimal combinations of factors that drive the best results and inform how to scale. The A/B test divides marketing into test and control cells, and the response is then compared to pick a winner. This approach is simple and effective, and given sufficient volume, can be turned into a learning factory for the organization.

Finally, develop and deploy a holistic customer-centric marketing analytics framework that will allow you to consistently track, measure, manage and optimize all activities occurring with your customers across all marketing and sales channels. This will provide visibility into the overall results and allow you to make more informed decisions on how to effectively grow your installed base.  Don’t forget to optimize your customer contact strategies and cadence on a continuous basis.

To learn more about building a Marketing Analytics Framework, Click Here.


If traditional technology vendors aren’t accurately anticipating the needs of their customers or understanding their risk of defection, they are at greater risk for disintermediation by new entrants or competitors who do.

Having an agile plan to go-to-market against market disruptors by building a customer-centric approach to cross-selling will be key to success. Check out our latest whitepaper on “The Last Mile Opportunity,” for 5 transformational principles to scale operations and build revenue success in the “last mile” of the customer buying journey.

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