9 Requirements for Effective Cross-Selling in Financial Services

As a part of their Future of Financial Services series, the World Economic Forum recently released a comprehensive and far-reaching report on the “New Physics of Financial Services” and the impact that digital transformation and the rise of Artificial Intelligence is having on the financial services ecosystem.

There is no doubt that these trends will change the operating models for certain firms and continue to impact the competitive dynamics of the industry in a number of different ways in the medium-term.  In the short-term, they are creating challenges and presenting opportunities for how traditional FSI’s acquire, grow and retain customers.  This is especially true in the area of cross-selling and retention. If traditional FSI’s 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.

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 generally estimated to run from 3x to 25X more expensive than cross-selling, the economics of cross-selling are very compelling.  Recognizing this, cross-selling has become a strategic priority for many financial services firms in recent years – yet many firms still appear to be far from realizing the potential of cross-selling.

Why is this? Some firms may be hesitant given the number of actions and warning directed towards FS firms contained within the CFPB Enforcement files where the cross-selling culture was perhaps a bit too aggressive – “Detecting and Preventing Consumer Harm from Production Incentives” as they refer to it.

For others, it may be the challenges associated with overcoming organizational complexity that spans multiple lines of business, diverse functional areas and disparate technologies and business processes that must be coordinated to deliver effective cross-sell programs.

In many instances, it may be the fact that cross-selling responsibility is often left to the “last mile” (the end of the buying journey) in that relationship managers or sales resources often simply don’t have the time or skills to effectively implement programs at scale. Or, efforts are driven by product owners who take a product-centric view of cross-selling as opposed to the customer-centric view of successful cross-selling programs.

Here then is our list of nine requirements for building effective and scalable cross-selling programs in the financial services industry:

1) Adopt a customer-centric view.

Too many cross-sell programs are still organized around lines of business and driven by a product-centric view of cross-selling. 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.

Patently obvious, but 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 and data lake architectures to quickly build data repositories. This allows data science teams quick access for specific use cases without processing overhead associated with large inflexible data warehouses. Liberate insights from the tyranny of workflow tools and 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 totality of their relationship with you and reflecting an understanding of their needs. Maintain assignment of segments and personas in your customer database to ensure 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.

Use an agile, reproducible approach to developing and managing a library of predictive cross-selling/retention models. Consider segmentation, RFM, CLV, next logical product, retention, Marketing mix optimization, among others.

Customer growth, share growth, wallet growth, account expansion—all of these strategic goals beg the same question; how do I get a given customer to buy more, or buy something new? Cross-sell models use data about the current installed base and compare this with data on other accounts that have upgraded. These are a close cousin to market basket models on the consumer side, analyzing how customers’ ”baskets” of products typically evolve as new items are added.

Deploy a disciplined, scalable approach to managing your data science operations to ensure reproducibility, scalability, and accountability of your investments in AI.

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 brand, what competitors are selling into those accounts and what new disruptors are emerging.

Best-in-class FSI’s leverage “always-on” market intelligence capabilities. Those that track customer feedback, competitive movements, and emerging disruptors. This intelligence is fed back into the product development process, innovation centers, marketing messaging, Account-Based Marketing activities, and sales enablement programs.


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

Today’s FS 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. Think of a potential buyer researching new savings and investment options to kick off 2019. This buyer can easily research opportunities online, get side-by-side comparisons from financial providers, chat online or over the phone with an investment expert, and then set up an appointment at the bank or financial institution 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 or even retaining those customers goes down considerably. Utilizing a consistent framework and taxonomy to map 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, 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 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 FS Cross-Sell 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 SaaS 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. Then, writing quick integration layers for specific systems. When that next great piece of technology is rolled out—or when Salesforce raises its prices by 20%— it’s no problem.  It just requires updates to an adaptor layer, vs. 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 proforma 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 line of code is written or a query is executed.

To learn more about Measuring Return on Analytics, Click Here

Implement agile pilots using test and learn methods such as A/B testing to quickly gain insight into optimal combinations of factors that drive the best results and then scale.  As every direct marketer’s learning method, the A/B test divides marketing into test and control cells, and the response is then compared using simple z-tests of proportions 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 of the activities occurring with your customers across all products, 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. Dont forget to optimize your customer contact strategies and cadence on a continuous basis.

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


Remember this: “If traditional FSI’s 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.

Download the whitepaper:

4-Step Approach to Cross-Selling into Mid-Market Accounts

In our recent CMO Survey blog post, we highlighted how Tech CMOs allocate three-quarters (74%) of their total marketing spend on their top priority: Driving growth from existing markets. This blog tells the story of HOW to get results driving cross-sell in those existing markets…using the experiences of a leading technology platform provider for digital and mobile payments as the hero of our story.

Want more detail? Download a PDF at the bottom of the page

Tech firms offering digital and cloud-based solutions (should) have great datasets! Not only tradition data on transaction frequency and spending levels but also IoT-related data on location, device type, and specific event triggers. With this high volume of customer, product, and transactional history the power of advanced marketing analytics offers a significant lift for cross-sell programs. This is particularly true in the SMB and mid-market customer segments, where accounts can number in the tens of thousands, coverage is broad through a network of resellers and partners, and account knowledge is diffused.

So how did one of our customers solve for this?

The Challenge:

Low sales rep productivity penetrating mid-market with a growing product line.

For this technology payments firm, their typical mid-market account manager was responsible for well over 100 accounts each and their ability to identify, prioritize and target cross-sell opportunities in their account portfolio was limited. Like most sales people, they knew their top accounts very well, but very quickly their account knowledge diminished as they went deeper into the portfolio (which is where much of the latent growth potential lies).

Meanwhile, Marketing would run monthly product-specific campaigns to mid-market prospects to source new leads for account managers. As a result, any single account manager’s ability to effectively, efficiently and consistently prioritize their outreach was limited. “Surfing” across the white space in their account roster while waiting for qualified marketing leads to be passed over was not delivering the required productivity. With new products being launched and competitive pressures rising, the company realized that they needed a data-driven approach to account coverage. This would maximize their cross-sell opportunity in the mid-market installed base while enabling sales and marketing productivity gains required to grow.

The Solution:

A 4-step approach to drive customer engagement and trigger qualified opportunities to sales.

We worked with our Tech client to deploy product propensity models enhanced with customer buying signals for each product across their portfolio. Scores were developed and updated weekly to supply prioritized opportunities to the account managers covering mid-market accounts. This approach was combined with continuous lead nurture campaigns based on product propensity—not an arbitrary outreach cadence—to drive engagement and trigger more qualified opportunities to sales.

Below are the 4 solution steps in more detail:

  1. Product Propensity Analytics: For each of the major product lines we developed product propensity models. These models evaluated the characteristics of clients who had previously adopted select products to identify the characteristics most predictive of product adoption. Had usage passed a certain threshold? Were there recurring service issues? Had revenue grown substantially? What other products in the portfolio were predictive of the need for additional products?This required gathering data from multiple different systems into a marketing data mart, including product usage data, service and support case files, firmographic information, contract data, and even credit data. These models were deployed to “score” underlying product propensity for a given product. This helped answer the question of what products should be offered.
  1. Customer Engagement Insights: The propensity models were supplemented with customer engagement data to develop a hybrid product opportunity score that reflected both underlying product propensity (the what) – as well as current levels of customer engagement that were predictive of current need or intent (the when). Was the customer engaging with product information on the website? Did they respond to a campaign? Were they searching for a competitive solution online? By consolidating additional internal and external signals and updating scores on a regular basis, the models added a current engagement component to the underlying product propensity, providing a consolidated view of both the what and the when. The entire account portfolio was re-scored on a weekly basis for all unpenetrated products.
  1. Triggered Outreach: Each week, the top opportunities were “triggered” to the account managers and telesales reps. Using agreed-upon business rules including account assignment and product recommendation, the top 30 opportunities for each account manager were “flagged” within salesforce.com and assigned to the appropriate resource for outreach. Model scores and related insights were updated on the opportunity record so each account rep knew why that customer triggered for a specific product that week. Reason codes for model scores were displayed in plain English, providing context for the account manager as to why the recommended product was a good fit, and the recent engagement activities that were driving the current week’s trigger.These insights were key to driving adoption of the solution and provided the context that made the account manager much more effective in their outreach, as well as confident in the validity of the score.This solution leveraged current capabilities within Salesforce.com, and beyond the addition of several custom fields on existing objects, required no additional technology to implement.
  1. Lead Nurture Support: High propensity opportunities with low engagement that were not yet ready for sales outreach were placed into “always-on” nurture campaigns – as opposed to the previous monthly product-based cadence. These opportunities were fed into Eloqua for execution on a weekly basis as well. Once customer engagement surpassed a certain threshold, these opportunities would be triggered for sales outreach, based on the defined set of business rules. This solution aligned sales and marketing around prioritized needs across the portfolio vs. the monthly product campaign architecture that had been in place previously.

The graphic below illustrates the approach that was used to implement the solution.

Opportunity Routing

The Result:

Cross-sell win rates improved by 34 points from 12% to 46% in the first 8 months.

When prioritized opportunities were “pushed” into Salesforce.com every Monday morning, sales performance improved almost immediately. After a brief pilot period with a handful of reps, the program was quickly scaled across the entire account management organization. In the first eight months, the win rate on cross-sell opportunities increased from 12% to 46%.

The account and opportunity intelligence from the predictive models that were provided in Salesforce.com were supplemented with targeted content and messaging for the specific product recommendation and the unique customer segment. This provided account managers with both the insights and the targeted content and messaging they needed – all on the same object within Salesforce.com. Similarly, this same segmentation was used to target all lead nurture messages through Eloqua, ensuring consistency across the entire buyer’s journey.

The realignment of marketing to support this data-driven approach to customer engagement was a significant enhancement to the previous calendar/product-based approach to campaigns. The result was a much tighter integration between marketing and sales, with marketing focused on nurturing customers over time to improve customer engagement around high propensity products. This end-to-end process also allowed marketing and sales to quickly dial up or dial down activity each week depending on changes in sales capacity, marketing priorities or other business requirements.

Cross-Selling is an Endurance Run, Not a Sprint

This month, Chase Sapphire signaled a new strategic focus on cross-selling with a lucrative 60,000-point signup bonus for customers opening a new Sapphire Banking premium checking account. In addition, the offer includes special VIP access to Sapphire lounges at concerts, sports and special events as well as early ticket sales and premium seats. The irony is that this offer is coming after Chase spent the summer scaling back and devaluating many of the loyalty offerings for the coveted Chase Sapphire cards, namely the favored Reserved card among millennials. So what gives? We think we have an idea.

Spin the clock back two years to August of 2016. Chase rolled out their Sapphire Reserve card with a rarely heard of 100,000-point signup bonus inside Chase’s Ultimate Rewards program, with travel perks and credits that sent the millennial demographic into a viral online frenzy. To put the cherry on top, the card was released in metal form to mimic the air of prestige often associated with wealthy and elite cards. The result was a wave of new acquisitions our market intelligence was picking up on back in September of 2016 (See Figure 1), and were able to report out to our clients in the Financial Services arena. (Several of whom promptly converted portions of their card line to metal.)

Figure 1: Market Intelligence reporting in 2016 on Chase digital discussions

Since that time, pundits and financial bloggers have written extensively that Chase’s lucrative rewards for Sapphire customers cannot have been sustainable for the company. Indeed, Chase has reported losses on the 100K bonus offering and has taken steps since then to scale back the number of signups allowed. Then, this summer they rolled back so many benefits that cardholders began calling it the “summer of non-loyalty” and suggesting they might actually begin considering leaving the Sapphire brand altogether. Competitors began circling like vultures thinking this might be the final nail in the coffin and a means to acquiring the massive millennial demographic Chase has been in control of for some time.

This past month, the volume shifted however, as our market intelligence teams began noticing volume trends around the Sapphire brand not dissimilar to those back in 2016. Conversations about Sapphire regaining the “halo-effect” were noticeable.

Figure 2: Sapphire Banking discussions last month

What our market intelligence indicated—and which Chase has since talked to—is a strategic play to first acquire a given target base and then work to develop them into both lifelong and higher value customers. Three key factors should be seen in their strategy:

  1. Initial acquisition costs may be significant – Not unlike Amazon’s strategy in the Kindle days, or their Prime rollout, Chase understood that initial lucrative offers might not turn an immediate financial return, but they will return a massive onboarding of clients. The initial 100K signup bonus with a slate of other massive perks was not sustainable, but it achieved its goal in driving millions of millennials into Chase’s brand.
  2. Evaluate the trade-offs today for the rewards later – Chase’s long-term strategy isn’t simply the two years from 2016 to 2018. Their vision is even further down the road – more than simply having millennials open checking accounts with Chase. Indeed, according to Chase’s own commentary, the offering of VIP access to concerts and early ticket sales in Sapphire Banking offers TODAY is intended to yield customers who will want wealth investment and lending services of larger sizes in years to come.
  3. Think “ecosystem” as opposed to simple “cross-selling” – Similar to Apple’s strategy to supply your phone, watch, laptop and tablet need on a common operating system… Chase is combining their card, banking and soon to be redesigned digital platform into an ecosystem where Chase’s goal is to own the entirety of the customer’s financial services needs and not simply be their preferred card provider. And the result is paying off. Chase is reporting at current a 75% active payments user rate, 48 million cardholder base, more than 50% of Zelle transactions, greater than 70% mobile wallet integration and a 22% credit card market share.

Chase is clearly taking the “long view” of cross-selling. We’re continuing to watch Chase closely as they redesign the customer financial experience with a long-term, cross-platform Chase brand experience.

For more on cross-sell, read our series on “How to Cross-Sell at Scale” Part 1 and Part 2

How to Cross-Sell at Scale – Part 2

By now, everyone knows that cross-selling (including upselling/cross-selling a new product) is an unbelievable source of profitable revenue growth. Yet, there is a challenge. To be successful, a cross-sell sales play or marketing campaign must provide highly targeted, very tailored offers to each prospect. “Carpet bombing” (oversaturating) existing account buyers and prospects with company-specific messaging won’t work; you’ve got to hit the right buyers at the right time with the right offer and right content. Simply put: your buyers know you, and they expect you to know them.

In Episode 6 of our Killer Slide Series short video, we walked through the below customer intelligence platform we help companies develop to scale cross-selling efforts. In short form, marketers and sales reps need to answer four questions, and without automation, that requires a rep or marketer to spend at least 20-30 minutes per prospect researching as many as 10-15 different data sources for answers. That’s not scalable…period.

The methodology we use (we call it PlayCaller), answers a basic set of questions needed to drive cross-sell:

  • Who should they target this week?
  • What product(s) should each prospect be offered? What is the best content needed to advance and close a deal?
  • How and how often should they be contacted (i.e. channels)?
  • Where are we achieving measurable success?

How to Cross-Sell at Scale - PlayCaller Methodology The general approach to answering these questions is outlined in the above graphic, but it’s how this gets scaled and acted on that’s critical. In this blog, we focus on three key components to the cross-sell intelligence platform: 1) Data Sources, 2) Decision Analytics, and 3) Activating in Workflow.

1) Data Sources:

Most companies likely already have the critical data sources they need to double or triple their cross-sell effectiveness. The challenge is integrating these data together in either a structured data warehouse or a semi-structured data lake. Four of the most powerful sources of cross-sell data (or “signals” as we call them) include:

  • Purchase History: Purchase history includes timing and cadence, what was specifically bought, and prices paid. These are obviously valuable data, but sometimes the analytics are surprising. Did you know that oftentimes increased purchase frequency is a strong predictor of customer flight to a competitor?
  • IoT/Product Usage History: As IoT and other usage tracking technologies explode, these big data have already become a powerful signal identifying which customers are ready to be sold to.
  • Customer Service Inquiries: By tracking both service needs and complaints, product upgrades and cross-sell can turn around client dissatisfaction.
  • Web Visits and Downloads: Your existing clients visit your website more than anyone. Tracking who is reading what—and following up with highly relevant “add-on content”—can turn content consumption signals into new deals.

2) Decision Analytics:

Too often, companies deploy basic machine linear models, such as optimizing which customers should be mailed to in order to maximize ROI, and stop there. But when it comes to data science, simple linear thinking just doesn’t cut it today. Marketers and sales channels need to know exactly which customers in their territory are ready to buy what products, and through which channels they want to be sold to. MarketBridge typically starts with four models when building cross-sell platforms for our clients:

  • Buyer Segmentation: There are usually 5-7 buyer types present in a given industry. These clusters are typically driven by functional need (what), psychographics and buying style (who), and channel usage (where). Understanding and scoring these segments helps attain better cross-sell performance by getting the right content and offers to the right buyers. For more detail, check out this blog on content segmentation and this approach to buyer segmentation.
  • Buying Proclivity: The proclivity to buy helps determine when to send a specific “action” outreach vs. a nurturing, “teaching”-type outreach. The basic elements of RFM (Recency, frequency, monetary value) analysis are typically critical inputs into this score.
  • Next Logical Products: Understanding the specific SKUs and bundles of SKUs that a buyer is likely to need next helps drive relevancy.
  • Customer Attrition Risk: The risk that a contact, buying center, or entire account is about to stop buying is critical. When a “warning level” is reached, be prepared to spend more on high-value touches to intervene. The best attrition-avoiders validate, research, and respond to attrition warnings, in-person if necessary.

3) Sales & Marketing Activation:

The best data and machine learning are useless unless they can be easily understood and acted upon by your sales & marketing channels. Delivering predictive analytics into your existing customer contact workflow platforms is critical. We have found that loosely coupled architectures are dramatically better over the long run than tight integrations with SaaS martech platforms. Think about it—if you’re using the exact same sauce as all of your competitors, you won’t be able to maintain your advantage. This is what the SaaS vendors want, of course—for everyone to be on their system, using identical proprietary algorithms.

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

The better alternative is to deliver analytics via a set of standardized endpoints that any CRM or martech platform can use, and then writing quick integration layers for specific systems; this is the MarketBridge approach. This way, when that next great piece of technology is rolled out—or when Salesforce raises its prices by 20%— it’s no problem. We just need to spend a couple of days writing an adaptor layer, vs. 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-sell recommendations also share the same DNA. Typically, the API calls for cross-sell include several microservices that, when taken together, form the basis of the contact / content strategy woven into the CRM / Martech platform. We’ve listed a few of the most common and useful here:

Element Question Response
Account Top cross-sell contacts? Ranked list of contacts
Contact Segment? Segment for this contact
Contact Top products? Ranked list of products
Contact Likelihood to attrit? Probability
Product-Segment Right offer? Offer structure
Product-Segment Right content? List of top content pieces

In summary, this framework should help sales and marketing executives think about cross-sell in a systematic way, and set about driving continuous improvements across all three.

  1. What data are needed to derive the signals that make good cross-sell decisions, and how do we go about getting them all in one place, relatively cleanly, and keyed to the level where data scientists can use them for modeling?
  2. What questions should executives be answering with analytics and data science, beyond the basic “scored list” approaches that dominate the space today?
  3. How can I get data out of and into my operational systems, without tightly coupling?
  4. How should I measure the end-to-end process across platforms and use that information to optimize my performance?


Episode 6: Building a Scalable Cross-sell Intelligence Platform

The Killer Slide Series on Data-Driven Revenue Growth

In Episode 6, MarketBridge’s CEO discusses how to build a scalable cross-selling engine by applying machine learning and analytics in making sales and marketing decisions. Businesses’ existing customers expect sales reps and marketers to deliver more personalized outreach than ever before. With the hundreds of data points available across systems and technologies, “getting to know” each cross-sell prospect requires tons of preparation before a single outreach can be made. Watch this video to learn how we built a platform that streamlines intel aggregation and executes on normally “human-only” powered decisions.

First, we walk through the four “decision steps” a sales rep or marketer must make to know who to target, what offer to provide, how to reach each target and how to report on results. By gathering signals through a customer cloud and driving that intel through existing sales and marketing platforms, businesses can efficiently and effectively double conversion rates.

We’re here to help! Chat with us on how we combine our human expertise with machine learning to streamline cross-selling:
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How to Cross-Sell at Scale – Part 1

Cross-selling is the fastest, most profitable path to incremental revenue growth, period. With existing accounts and existing buyers, companies already have contracts in place, relationships established, and the data needed to identify new revenue opportunities. Assuming a vendor only has a 30% share of the total addressable market (TAM) in an account, attaining just 5% more in account share grows account revenues by 17%.

Given the clear ROI, why do so many companies have trouble getting cross-sell campaigns off the ground and scaled?

Two reasons: First, marketers mistakenly assume a new software tool such as ABM or discipline such as predictive AI will solve the problem by itself. It won’t. Secondly, sales leaders underestimate the upfront time and effort an individual account manager or sales rep must invest to plan out their cross-sell play. Consider two types of cross-selling:

  1. New Product, Existing Buyer: While this may be the easiest cross-sell, it still requires the sales rep to research of which existing buyers are candidates for which new products. Then, they must get trained on the new product(s) and be comfortable enough to sell a new product or service without risking the existing relationship.
  2. New Buyer, Existing Product: In cases with larger, enterprise clients there are often multiple new prospects across departments, business units, and geographies who could buy the same product or service. Once again, too often this requires sales reps to comb through many internal data sources (purchase history, product usage, customer service logs) to identify new prospects in an existing account.

The issue? When cross-sell research, call prep, and “relationship risk” become big challenges, sales reps (direct and 3d party) revert to selling only the products they know to the people they know. Simply stated, they won’t aggressively cross-sell. If they can meet their quotas with existing buyers and products, then why cross-sell?

To cross-sell @ scale, product marketers and sales ops leaders must take as much of the cross-sell prep work (buyer profiling, selection, product recommendation, tailored content) off the plate of the sales rep. I call this providing sales reps with “prescriptive sales plays;” plays that define in each territory who to target, what message to send, and what product(s) to recommend. These prescriptive sales plays can be developed by a centralized research and analytics service bureau (in-house or 3rd party) and pushed to sales reps and customers through existing CRM and marketing automation systems.

In sum, cross-selling ain’t easy because it requires data intense prep work. But if you can simplify the cross-sell process for sales reps, then revenues and profits can soar. In part 2 of this blog, I will add the “how…”

Two “Magic Numbers” for Every CEO and Sales & Marketing Leader

As nearly every company aspires to have recurring revenue business model, investors and analysts are increasingly focused on two “magic number” metrics: ARR/CAC and NRR. More importantly, every Sales & Marketing executive and employee should be fully aware of these numbers.

  • Customer Acquisition Payback (ARR/CAC): Customer acquisition effectiveness is increasingly being measured by expected Annual Recurring Revenue (ARR) divided by Customer Acquisition Cost (CAC). For many companies, just exceeding a ratio of ARR/CAC greater than 1.0 is a victory. What proponents of a > 1.0 ARR/CAC assert is that “this company is willing to spend every dollar of 1st year revenues to acquire a new customer.” Why? Because if a company truly has a recurring revenue model with acceptable gross margins, retaining that customer through years 2-5 is a profit machine.
  • Net Customer Retention (NCR): Customer retention effectiveness is a combination of YoY customer renewal rates plus cross-sell driven share-of-wallet increases – and it must be over 100%. Most companies consider annual renewal rates of >80% to be successful. A natural 20% attrition can be expected due to changes in decision-makers, financial priorities, and individual/corporate “death.” But to offset natural attrition, companies must not only provide great service but also cross-sell other products and services to increase share-of-wallet within 80% of customers renewing each year. A >100% NCR eliminates the “leaky bucket” that can drain a company’s YoY revenue base.

The two magic numbers are fairly easy to calculate – but a lot harder to achieve and sustain. The three questions every CEO and Chief Sales & Marketing Officer need to answer are:

  • How are we performing vs. these two “magic numbers”?
  • What operational levers can we pull to drive improvement?
  • What investments in scalable technology are we making to accelerate performance?

More on these questions in future blog posts.


Cross-Selling: A Gold-Mine for Incremental Revenue

We work with multiple clients and over and over have come to understand the importance in cross-selling and how it impacts bottom line. The facts are simple – from advertising, educating prospects and all the steps needed to nurture a new lead to the point of trust – new customer acquisition is costly. Acquisition is typically 3-5x more expensive then cross selling into the existing account base.

Our Assertion?

Cross-selling accounts for greater than 70% of most B2B company’s annual incremental revenue growth and over 25% of total revenues each year.

And, there are two basic types of cross-selling:

1. Selling to more products to existing buyers
2. Selling to more buyers in existing accounts – a goldmine for revenue and profit growth

So, why do most companies tend to over-invest in new customer “acquisition?”

Why require significant investment of marketing and sales resources and when you could invest more in cross-selling to “known buyers” – where firms are more likely to grow?

Cross-selling is a challenge because existing customers – accounts or buyers – expect their suppliers to know them well. They expect quality interactions, requiring tailored engagement and personalized offers/content. But too often, existing customers are “orphaned” because sales and marketing teams lack complete customer information or don’t have the ability personalize content and offers.

Consider This: How many of your existing customers are “marketing email suppressed” because sales is worried about marketing damaging the relationship? This is the case more often than you think. For those that marketing can touch, how many customers receive generic messages, content, and offers that lack relevance and specificity?

How to Win:

Successful cross-selling requires companies to power BOTH marketing and sales teams and not fear the additional outreach (from either marketing or sales).
3 things your teams need:

  • Aggregated Data: This includes detailed account profiles, buyer/user profiles, historical interactions, product purchases, usage data, and other data to increase customer knowledge and drive relevant messages. It’s about more than CRM data, and includes the integration of internal and external data to provide a robust picture of the customer.
  • Analytics to Prioritize Targets, Content, Offers: Your teams needs to develop and deploy a battery of “predictive analytics” that flag customer needs, likely next purchases, and attrition risk, arming marketing and sales teams with the triggers and prescription they need to take action.
  • Customer Engagement Tools: Tools that allow you to remain front and center for existing customers, so you are there when they are ready to buy. Anticipating your customer’s needs and engaging at the right time is crucial, independent of the channel your customer prefers. After all, your competitors don’t stop marketing to your customers!


Ultimately, there is massive potential for organizations to “crack the code” on cross-sell…

However, because of the inherent challenges in getting it right, most organizations fail to realize this potential and are underwhelming their existing customers in the process. The best organizations solve this problem through improved customer data, predictive analytics, and focused outreach to customers via their preferred channels.

4 Ways to Drive More Revenue Through Cross-Sell

There is no better way for B2B organizations to drive growth than through selling to their existing accounts. Despite the potential returns, most organizations leave this strategy almost entirely in the hands of their sales teams without putting the rigor and discipline to be really successful. Unknowingly, they are leaving a huge opportunity on the table…

The best companies have built and run plays which explicitly target cross-sell in a programmatic way, combining resources from marketing and sales to dramatically improve performance.

These cross sell programs generally fall in one of four categories:

1) Traditional Cross-Sell – sell more of the portfolio bundle or products set to existing buyers.

  • Why this works: What is easier than selling into a buyer who uses your product/service and values you? For multi-product business models, selling across your portfolio drives immense revenue
  • Why this can be hard: Sometimes the perceived risks in selling to an existing buyer get in the way of the obvious opportunity. Often the buyer sees you as a “one-trick-pony” and questions the value proposition of a new offering.
  • Secret sauce: Creating a complete profile of each existing customer and building trigger events around their buying moments can help inform your team to when and with what product/value proposition to cross-sell.

2) Divisional Cross-Sell – sell across multiple divisions, regions, or functional areas within an existing account.

  • Why this works: Nothing is more powerful than a referral, except an internal referral with a case study that has worked in the business. And maybe Superman.
  • Why this can be hard: Too often organizations focus on selling across all potential buyers with using the same value prop instead of customizing their approach — focusing on the right buyers, those that are ready to buy, and personalizing the offer or solution.
  • Secret sauce: Understand the structure and buying groups within your existing customers, and focus on those who can actually buy from you, with an offer that reflects their business needs.

3) New Product Cross-Sell – seeding the success of a new product launch by positioning and selling to existing buyers.

  • Why this works: When new products are developed the right way, they naturally align to specific buyers who will benefit from its features. When these are positioned to existing buyers, the combination of the products value and your existing relationship can produce incredible results.
  • Why this can be hard: The hardest part of launching new products to an existing customer base is helping sellers develop confidence in the new product, in terms of understanding the product and its value, accessing the right information to share, and also confidence on its fit for the existing customer.
  • Secret sauce: While you must target the right customers for each new products, enabling sellers with the right collateral and knowledge is often the main driver of success. This includes making case examples and product brief easily accessible to the team for more efficient and effective outreach.

4) Upsell of An Existing Contract – growing the value or features within an existing contract with an existing buyer.

  • Why this works: Adding features to a solution or product should add value (and thus price point) to grow the relationship with an existing buyer.
  • Why this can be hard: If incremental value is not positioned effectively (or well understood by the seller or customer), there is often major resistance around price increases with customers. Further, there is often organizational pressure on the customer side to reduce total cost, independent of incremental value delivered.
  • Secret sauce: Using analytics to figure out which customers have a higher propensity to spend and which would value the incremental functionality is key. This information will allow you to prioritize where to drive price increases and how to position new features.

Understanding the type of cross sell you need to execute should influence the program you design and the play you run. Organizations who are really defining the right cross sell play for their business and systematically running these plays are seeing significantly better results.

Are there cross sell plays that you are running that are not in the four we have highlighted? Would love to hear from you on this or other topics related to this post!

Acquisition vs. Cross-Sell Economics: The No Brainer Investment Decision

Why is it that so many companies these days are over investing in customer acquisition?

Don’t get me wrong, acquiring new customers is critical to any business’ growth, but we all know that customer acquisition costs (CAC) can be extraordinarily high. Studies show that attracting a new customer can cost 5 to 7 times more than retaining an existing customer. All too often the payback period (when incremental margins exceed CAC) exceeds 12 months. If that customer doesn’t stick around for years, a lot of money has gone down the drain…

Conversely, cross-selling – selling more products/services to existing buyers – can have an incredibly high ROI. Assuming near $0 CAC, the cost-to-sell an add-on product or service typically has a payback period of <3 months. Now ask yourself, how many companies have an average customer share-of-wallet greater than 30%? Very few….

Here is a simple example: If a company has an average customer share-of-wallet of 25% and they increase that to 40% across just half their customer base, that’s 30% revenue growth from their existing customer base ALONE! And the incremental profits from each deal hits their bottom line within 90 days.


So why are people investing so much in acquisition vs. investing in cross-sell?

To be honest, acquisition is operationally easier and “sexier.” Today’s B2B marketing technologies – social media, marketing automation, email, webinars, etc. – make lead gen easy to automate, deploy, and scale, plus have a tantalizingly low “cost per lead.” But while Marketing teams can create tons of top-of-the-funnel volume and noise, once you consider conversion rates the cost of a closed lead skyrockets. A simple rule of thumb is that the cost per closed marketing lead is 30 times as expensive as a simple marketing qualified lead (MQL). The lead black hole and low conversion rates can just blow up CAC.

Conversely, cross-sell can be difficult to execute. As we will outline in future blogs – cross-selling has an incredibly high ROI but requires involving enabling sales reps, overcoming perceived customer relationships risks, and investing in rigorous analytics to make sure companies offer the right products to the right customers at the right time.

The lesson is simple – most companies should shift more investment from customer acquisition to customer cross-sell programs that are scalable and sustainable. We go in-depth on 4 different cross-sell plays your team can run in this blog.

Would love to hear your thoughts below…