AI-driven marketing use cases and watchouts

AI is transforming marketing, likely in ways we haven’t realized yet. From rapid content generation to programmatic advertising, marketers have obtained a new level of automation and insight that allows them to shift their focus to analysis and strategy. However, AI requires clean and comprehensive data at the foundation. One use case for the go-to-market data lake (GTMDL), the single source of truth between sales and marketing, is to power current and future AI use cases.

But what are the key building blocks for an AI-driven Go-to-Market Data Lake (GTMDL)? How are businesses leveraging cloud data warehouses and AI tooling to level up their marketing operations? What are the pitfalls? Let’s look at a few ways tech-led organizations are rethinking and rearchitecting their data, in view of the AI revolution.

Data as the foundation

Quality data is paramount for the underpinning of an AI infrastructure. Unsurprisingly, flawed input data leads to flawed analysis and output data. Without the proper attention to data quality, AI will simply provide the wrong results at a much faster pace. Many organizations fall into this trap – the best product in the world, either a CDP or homegrown solution, will fail if data architecture is not at the forefront of the design.

We believe the GTMDL is the answer to this problem. A carefully designed data lakehouse, tailored to your customers’ needs, serves as the foundation. The AI platform, integrated with the GTMDL, serves as the hub of activities and is where a Large Language Model (LLM), Retrieval Augmentation Generation (RAG), and other AI modeling are built and executed. With this base, AI operations can be executed with ease, providing content, insights, and recommendations in a fraction of the time it would normally take a marketing team.

Insights AI

A centralized GTMDL provides the bedrock: growth and scaling for both storage and compute. AI bridges the gap between humans and systems by putting the data at our fingertips. There are many insights to be explored, and AI tools are being capitalized on to provide these insights for marketers.

  • Underlying data are now queryable by non-technical stakeholders, providing natural language search to SQL systems and removing the IT hurdle
  • Predictive analytics churns customer data, both real-time and historical, anticipating future behaviors and calculating CLV
  • Reporting agents do much of the legwork required to distill customer data into dashboards, allowing for more focus on the details

Generative AI

Generative AI, or simply GenAI, is likely one of the first areas of AI adopted by marketers and we’re seeing it significantly boost productivity. For example, consider the lift required to leverage an existing blog post or whitepaper as the source of a targeted ad campaign. GenAI can produce as many versions of the concept as needed and in the necessary format―whether that be text, image, or video―in a fraction of the time.

Using commercially available or free tools such as ChatGPT is a common route for most marketers looking to get started with AI and is great for many cases. However, AI coupled with the GTMDL is beneficial as an augmentation for many reasons:

  • Data stays within the governance of IT, enhancing privacy and security
  • Content is generated from internal sources and is more relevant
  • Models can be trained and customized for different uses

Decisioning AI

How might AI enhance our decision-making process for something as simple as A/B testing? At the most basic level, AI can identify patterns in data that humans may miss, providing recommendations that will lead to more successful results. But we still must conduct the test and wait for the results, right? Not necessarily. An AI-driven GTMDL can be leveraged to learn on the fly and adjust recommendations. A single A/B test that may take 8 weeks can be accomplished in much smaller periods, such as 2 weeks, increasing the number of experiments within the timeframe. Response data from the test is continually received and ingested back into the model, informing us of the success of the test cases. AI decisioning subsequently adjusts the recommendations and provides alternate tests that are then adjusted in downstream campaign platforms. As we continue to feed this data back into our GTMDL, along with all the other data points we are gathering, we gain a deeper understanding of our audience and create a system that is nimble and responsive to the market.

Key watchouts

We’ve covered a handful of great use cases for marketing teams to implement an AI-driven GTMDL and there are hundreds more. We also should pay close attention to a few factors that will impact your outcomes, such as governance, cost, and data quality.

Governing how AI is used within an organization is important to reduce risk, protect sensitive data, and establish guidelines for responsible use. With AI in its infancy, it’s important to establish as many guardrails as needed without hindering the exploration process. One failure, such as improperly handling PII, will be devastating.

Be mindful of cost―AI is storage and compute intensive. Carefully architecting AI systems is important to control runaway costs and stay within budget. Start with small data sets that don’t require immediate results and 24/7. Also, enabling spending limits where possible is a must.

Most importantly, as stated previously, the data quality is crucial. The term GIGO (Garbage In, Garbage Out) may seem trite, but it certainly still applies. Investing significant amounts of capital in AI without proper oversight of the data will result in less effective, if not useless, outcomes.

Conclusion

Current and future AI uses for marketing and sales will require clean data and strong taxonomies and metadata. Smart organizations are building a flexible and scalable go-to-market data architecture that can be AI driven—now or in the future. Granular data in an organized structure readable by AI can power current use cases like propensity modeling and segmentation and prepares for future use cases like real-time media optimization.

Check out the GTMDL whitepaper here to learn our vision and approach to AI, data, and Martech. Data is the key to your success, and we can help!

Download the whitepaper, “Building a composable go-to-market data stack”​

Rethink your data foundation and lead the next era of AI-ready, insight-driven marketing.

Beyond the CDP: Building a composable go-to-market data stack

Beyond the CDP: Building a composable go-to-market data stack

Why top marketers are ditching the CDP for something better

Marketers sought a 360-degree view of the customer for years. CDPs promised a solution, but delivered a narrow lens, focused on audience activation, not insight, measurement, or strategic growth. As the pressure to use AI grows and budgets tighten, CMOs are realizing: software-based CDPs aren’t built to handle the real complexity of today’s marketing.

This paper introduces a new approach—the Go-to-Market Data Lake (GTMDL)—a flexible, scientific, and scalable architecture that places modern cloud data infrastructure at the center of sales and marketing. Unlike closed software platforms, the GTMDL is designed for how your business runs—enabling measurement, modeling, AI, and omnichannel activation with full transparency and control.

In this paper we cover:

  • Why CDPs failed to deliver: How the promise of one-size-fits-all software missed the mark for real marketers

  • The rise of data strategy as a marketing imperative: Why CMOs can no longer leave data to IT

  • What a GTMDL unlocks (use cases): From better sequencing of campaigns to full-funnel measurement and AI-powered decision-making

  • Designing for business value: How use-case-first development avoids long-running IT projects that are aligned to technical milestones instead of business outcomes

  • Laying the AI foundation: Why having clean, granular, and governed data is the key to leveraging current and future AI

Download the paper to rethink your data foundation and lead the next era of AI-ready, insight-driven marketing.

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What’s next?

Beyond the CDP: Building a composable go-to-market data stack

Marketing needs better data, not more software. See how a GTMDL can unlock real insight and growth—download the whitepaper.

Benchmarks to blueprint: How financial services marketers can elevate marketing execution

Marketing budgets are tighter and expectations higher. Get the data-driven blueprint for smarter, ROI-focused execution.

A new golden age for employee benefits

Employee benefits are at a turning point. Discover how GTM leaders can cut through complexity and unlock growth—read the whitepaper.

Inside BioCatch’s ABX strategy that targets the world’s largest banks

Challenge: not enough data

BioCatch is a world-renowned leader in financial crime prevention powered by behavior biometric intelligence, which uses advanced analysis of a user’s physical and cognitive behavior to help banks protect consumers and their assets from fraud and cyberattacks. 

BioCatch’s marketing team faced a familiar challenge: a lack of actionable data. This made it difficult to effectively connect with their ideal audience using personalized, relevant messaging.

“We didn’t want to be on an ad platform where we were wasting even a penny showing ads to people who didn’t care or were not within our ICP,” said Jonathan Daly, CMO of BioCatch.

Past campaigns leaned on more traditional marketing tactics, often generating leads that didn’t align with their ideal customer profile (ICP). Without a way to clearly understand buying signals and real-time intent, resources were being drained without measurable ROI.

Solution: implementing 6sense

To address this, we helped BioCatch implement 6sense and build out an ABX strategy to use this data.

Our team designed a series of one-to-few and one-to-many campaigns, integrated a multi-touch framework, and established a robust reporting framework for tracking full-funnel performance.

We began by refining their ICPs and deploying 6sense’s Predictive Analytics to continuously optimize messaging based on customer behaviors and buying signals. This AI-driven capability provided visibility into where accounts were in their journey, enabling BioCatch to prioritize high-potential prospects.

6sense’s Intent Scoring added another layer of precision, giving the team the data they needed to focus efforts on the accounts most likely to convert based on prior engagement trends.

Outcome: a wildly successful pilot campaign

We rolled out a pilot initiative with a bold target: engage 553 global banks that had shown little to no previous interest, and move at least 60 into the active sales pipeline—all through an Account-Based Experience (ABX) strategy.

Using 6sense, we developed over 200 unique audience segments and ran personalized one-to-one, one-to-few, and one-to-many campaigns.

Over the course of six months, we launched highly tailored landing pages, ran full-funnel, multi-channel campaigns across 6sense Display Ads, LinkedIn, and Google, and synced our messaging to match where each account was in the buying cycle.

In total, we created over 450 creative assets and built over 10 landing pages. And after six months, the results were:  

  • 5x increase in accounts in active pipeline stage  
  • 6% of the full target account list moved into the pipeline stage since March  
  • 63% increase in accounts in active engagement stage  

This initiative marked a turning point for BioCatch’s marketing strategy—transforming their approach from broad and traditional to data-driven and precision-targeted. By leveraging the power of 6sense and a deeply segmented ABX framework, BioCatch was able to focus its efforts where it mattered most, align closely with buyer intent, and drive measurable pipeline impact at scale. The success of this pilot not only proved the value of intent data and predictive insights but also laid a strong foundation for future growth.

The VAR-to-MSP shift: It’s time to eat egg salad

Growing up, when I heard the expression “humble pie,” I would always correct the speaker and say, “egg salad.” While super confusing to most, my parents understood perfectly—I LOVED pie and hated eggs. If there was something impossible to eat, eggs were my standing metaphor. Even now when I admit I’m wrong, I hold my nose, ignore the texture, steeling myself for some egg salad.

It was once trendy to say that “VARs are becoming MSPs.” For a while, it even looked true. Around 2015, the writing was on the wall: the traditional value-added reseller model was under pressure. Product margins were collapsing, cloud was displacing boxes, and recurring revenue was the new gold standard. To survive, the logic went, VARs would transform into managed service providers (MSPs). They would trade one-off project work for sticky, managed service contracts. They’d adopt SLAs, build helpdesks, and evolve from sales-heavy shops into operationally efficient service providers.

But in 2025, it’s time for the egg salad: most VARs never really made the jump. The ones that did are thriving—but they are the exception, not the rule.

The Seductive Simplicity of a Linear Story

This “evolution” narrative felt inevitable because it tracked with everything the market told us to value:

  • Predictable recurring revenue
  • Higher valuation multiples
  • Greater customer lifetime value
  • Alignment with cloud-first buying behaviors

Private equity bought in. Vendors retooled their partner programs. Analysts drew funnel diagrams with VARs metamorphosing into MSP butterflies. But underneath it all, the operational DNA didn’t change.

You can add a helpdesk to a VAR, but that doesn’t make you a service provider. Selling an RMM agent doesn’t mean you know how to run a co-managed IT environment. Most VARs bolted on services, but never restructured for operational scale

The Data: Divergence, Not Convergence

Let’s look at how MSPs and VARs actually allocate their time and revenue across service lines. A visual comparison of 2025 estimates tells the story clearly:

Chart data synthesized from publicly available reports including Canalys (MSP Landscape 2024), CompTIA (State of the Channel 2023–2025), Kaseya/Datto MSP Benchmark Reports, and IDC Partner Ecosystem Forecasts. Figures are directional estimates reflecting market share by service line and are rounded for comparative visualization.

This isn’t just a surface-level difference—it reflects a complete divergence in operating models. MSPs are anchoring themselves in scalable, automated, recurring service delivery. VARs remain largely tied to hardware, implementation, and short-term projects.

Where MSPs are optimizing for margin per ticket and time-to-resolution, VARs are still chasing margin per unit sold and quoting cycles. This graph is less a snapshot than a roadmap—the MSP economy is moving in a fundamentally different direction.

Why Most VARs Didn’t Make It

  1. The Culture Gap: VARs are project-based. They optimize for margin on discrete transactions. MSPs are operational entities. They think in workflows, SLAs, and margin per ticket. That shift isn’t just financial—it’s organizational. And many VARs didn’t want to make it.
  2. The Tech Stack Problem: MSPs build around RMM, PSA, MDM, and now AI-driven automation. VARs, meanwhile, are often stuck quoting hardware and maintaining legacy relationships with distributors. You can’t bolt managed services on top of that stack—you need a replatforming.
  3. The Talent Trap: Great MSPs invest in service delivery talent—L1, L2, and increasingly virtual CIO roles. VARs hire for pre-sales engineering and deal support. The skillsets are different, and so is the hiring motion. You can’t just retrain a sales org to run managed services.
  4. The PE Playbook Wasn’t Enough: Yes, private equity firms tried to MSP-ify their VAR portfolios. Some succeeded. But many just bundled services with no operational integration. They got a few years of EBITDA uplift, but not the long-term transition they expected.

What Actually Happened

So if VARs didn’t become MSPs, what did they become?

The answer depends on how aggressively they evolved:

  • The Bold Few replatformed and built true MSP engines. These are now indistinguishable from born-in-the-cloud players.
  • The Middle Majority added services but remained sales-centric. These firms are being commoditized or acquired.
  • The Legacy Holdouts stuck with project work, hardware, and on-prem support. Many are now losing relevance.

Meanwhile, the MSP segment matured, specialized, and consolidated. We now see:

  • Vertical MSPs with deep IP in healthcare, legal, construction, etc.
  • MSSPs born from MSPs that doubled down on cybersecurity.
  • Platform MSPs that run integrated, repeatable service models across hundreds of clients.

A New Playbook for Vendors

If you’re a vendor with a cloud, SaaS, or hybrid HW/SW portfolio, it’s tempting to cling to the idea that your legacy VARs will modernize into service delivery partners. But that bet isn’t aging well.

Instead, consider this:

  • Segment by Operating Model, Not by History: Don’t ask, “Were they a VAR or MSP?” Ask, “Do they have the systems, people, and incentives to drive recurring service outcomes?”
  • Prioritize Integration into the MSP Stack: MSPs want fewer tools, deeper integration, and automated workflows. If your solution doesn’t plug into their PSA, RMM, or ticketing platforms, you’re just noise.
  • Lean Into Specialization: The fastest-growing MSPs are niche-focused. Help them go deeper: offer compliance bundles, co-branded vertical marketing, or SLAs tailored to end-client needs.
  • Design Programs for Stickiness, Not Just Margin: Margin incentives are table stakes. Design for long-term revenue growth: training, automation, customer success collaboration, and shared account planning.

A 2025 Playbook for MSPs

  • Productize Services: Bundle high-margin, repeatable services (e.g., MDR, compliance-as-a-service) that scale.
  • Automate Everything: Use AI and ML in ticket triage, patching, threat detection.
  • Standardize Stack: Fewer tools, deeper integrations—limit vendor sprawl.
  • Deepen Vertical Expertise: Create proprietary playbooks for specific industries.
  • Co-Manage Strategically: Partner with internal IT teams, not compete with them.
  • Invest in CS + Renewal Ops: Recurring revenue doesn’t renew itself. Customer success drives MRR durability.

A 2025 Playbook for VARs

  • Decide: Reinvent or Specialize: Either replatform into a true MSP or go deep into enterprise project expertise.
  • Bundle + Subcontract: Don’t try to become an MSP overnight. Partner with one and build margin into bundles.
  • Modernize Sales Motions: Sell lifecycle value, not just SKUs. Introduce consumption-based offerings.
  • Align with Cloud & Security: Even if project-based, lead with what clients are prioritizing—zero trust, hybrid cloud.
  • Offload Low-Margin Services: Get out of break/fix, generic helpdesk, and backup unless fully automated.

The idea that VARs are becoming MSPs was a useful bridge story—but it’s no longer true in most cases. Instead of hoping for convergence, it’s time to embrace the divergence. I am never going to eat egg salad, but a nice fried or scrambled egg may make the cut.

2025 B2B sales benchmarks

2025 B2B sales benchmarks

High-growth sales teams don’t just execute better—they think differently

What drives B2B SaaS sales teams to outpace their peers and achieve 20%+ YoY revenue growth? They’re not just working harder—they’re approaching sales with smarter strategies and tighter alignment. This first edition of our annual survey uncovers the mindset, tactics, and structures that set these high-growth leaders apart. Designed for sales leaders and CROs, it provides a clear roadmap to evaluate and activate growth opportunities with precision.

This report covers

  • Key differences between sales team archetypes: Steady Builders, Market Contenders, and Growth Leaders
  • Essential attributes of high-performing sales organizations
  • Building blocks to advance to the next level of growth
  • Five priority actions for sales leaders heading into 2025

Select insights

  • 33% of high-growth companies set targets based on opportunity potential rather than existing revenue.
  • Growth leaders employ documented, long-term growth plans and segment-specific strategies while aligning closely with marketing teams
  • Leading sales teams operate with an average of three customer segments compared to two or fewer for lower performers.
  • Industry-specific targeting and account ownership strategies drive greater efficiency, with single account ownership boosting ACVs by 40% compared to hunter-farmer models.
  • Growth leaders align sales compensation with strategy, ensuring motivation and clarity of focus.

Whether you’re looking to optimize sales operations, align your team with strategic goals, or unlock the next level of performance, this report offers the clarity and direction needed to succeed in an increasingly competitive B2B SaaS landscape.

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The impact of AI on go-to-market strategies, programs, and investments

The impact of AI on go-to-market strategies, programs, and investments

Research and insights from high tech market leaders

Generative AI (GenAI) is beginning to revolutionize sales and marketing by enabling highly personalized customer interactions, automating complex processes, and providing deep data-driven insights. To explore this further, we surveyed high tech market leaders. The resulting insights can help inform the future of marketing and sales motions—and where to place investments to deliver more effective and efficient Go-to-Market (GTM) strategies—in the age of AI.

This report covers

  • Top areas of expected AI disruption
  • Timeframe for adapting new GTM models
  • Most promising areas for GTM disruption
  • Reimagining jobs to be done within marketing, sales, and strategy
  • Key inputs needed to optimize GTM performance in the AI era
  • Delivering on the promise—top areas of investment needed

Select insights

  • 60% of respondents believe changing “Competitive Landscape” is the top area of expected disruption.
  • Over 54% of respondents recognize the urgency to explore new growth opportunities and fund these initiatives more swiftly due to the rapid pace of AI innovation.
  • 58% of respondents predict the most significant change in selecting channels and routes to market.
  • While all leaders recognized the need for substantial investment requirements, not all agreed on where.

Whether you’re navigating the impact of AI on customer personalization, content development, or strategic agility, this report provides the insights needed to stay ahead of the curve.

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3 channel partner challenges hindering your revenue growth

With the tech economic slowdown likely extending into 2024, businesses must adapt their resources, budgets, products, and partners to the new selling environment. As buyers delay large transactions, subscription services that are cost-efficient or vital to daily operations (like SaaS for payroll) will gain prominence. Given tech firms’ reliance on channel partners to seize market opportunities and deliver value-added services, companies must ensure their partners can effectively develop and sell new Anything-as-a-Service (XaaS) solutions.

Our direct client feedback and survey responses revealed that partners often struggle to adapt customer experience and solutions to embrace new XaaS-driven revenue streams. In the pursuit of XaaS success, tech leaders face three prevalent channel partner challenges:

  1. Misaligned Go-to-Market Objectives
  2. Unmet Service and Delivery Expectations
  3. Lack of Data-driven Engagement Models

1) Misaligned Go-to-Market Objectives

Swift pivots to XaaS models can result in inconsistent and confusing partner strategies and programs. Whether due to a lack of strategic vision or a lack of partner communication, it’s not uncommon to find a company trying to run two partner program “flavors” at the same time—one for traditional on-premises sales (which might be a large legacy revenue stream) and another for XaaS selling (which has different channel partner program characteristics). Businesses that haven’t thought through where XaaS revenues will come from and which partners are best positioned will struggle to grow.

Partner sales channels deliver 3x more XaaS revenue than direct sales channels (Figure 1), but not all partners are created equal when it comes to XaaS suitability. Managed Service Providers (MSPs), Cloud Solution Providers (CSPs), and Independent Software Vendors (ISVs) are best positioned to deliver clear recurring value to line-of-business decision-makers because they are embedded in their operations, delivering always-on outcomes with the potential for “moment of truth” experiences. Traditional Value-Added Resellers (VARs) and System Integrators (SIs) are more transactional, with client interaction on an “as needed” basis with extended time between purchases. During economic slowdowns, VAR and SI partners are far more likely to experience delays in client purchases, hurting a company’s potential to drive XaaS revenues.

The Fix: Align Objectives and Deliver on New Goals

To remedy misaligned go-to-market objectives, there are two primary areas of focus. First, redefine and quantify where new as-a-service revenue will come from (in other words, prioritize your growth pathways). Second, once the market opportunity has been refreshed, make the necessary partner network adjustments to your channel strategy, capture new revenue, and focus on partners with stickier relationships with clients.

2) Unmet Service and Delivery Expectations

Partners’ struggles to meet service and delivery expectations have become more complex with the introduction of XaaS offerings. The days of simply selling and installing a solution are over. To maintain a subscription contract and potentially expand it with add-on services, partners need a broader set of skills for ongoing support.

While many traditional partners have tried to enhance their customer service abilities, this transition has been slower and more challenging than businesses initially anticipated. As a result, partner performance has suffered, leading to dissatisfaction among tech firms with their partners’ capabilities throughout the sales process.

The Fix: Enable and Train “XaaS-Ready Channel Partners”

To tackle this challenge, companies should enhance partner skills in new delivery models and recruit and enable top XaaS-ready partners. Expectations also need to be clearly defined for each partner type. Along with training partners, setting thresholds of competencies/certifications, tracking performance against those expectations, and intervening on an ongoing basis can course-correct each partner and raise the performance bar for each and all.

3) Lack of Data-Driven Engagement Models

XaaS solutions generate an abundance of data, yet many partners lack the capabilities to use these new datasets to deliver value for customers. Businesses must aid partners in harnessing data, conducting analysis, and prescribing better experiences. With only 30% of respondents “very satisfied” with how XaaS partners service their customers with great experiences, honing in on the data and using it to build a better experience is a first start.

The Fix: Build an Always-On Insight Engine

With subscription and hardware-as-a-service solutions, businesses have access to individual and aggregated customer usage data that was previously unavailable. Companies can use these insights to prescribe to partners precisely what message to deliver to customers based on usage behavior, but they must first invest in building the data analytics solutions to extract that data. We call this an “always-on insight engine,” one that feeds actionable intelligence to specific partners in a conveyor belt fashion. A constant stream of actionable insights (“Hey, partner. Here’s what you can do now and why.”) will not only strengthen the vendor-partner relationship but drive incremental sales.

Overcome Challenges in the Race to XaaS Success

CROs must refresh channel strategies to outperform the competition. To deliver the predictable business outcomes and customer experiences needed for a winning subscription model, companies must focus on finding the right mix of partners, enhancing those partners’ skill sets, and leveraging customer usage data.

Download our report, “A CRO’s Guide to Transforming the Channel for XaaS Success.”​

In this report, built from quantitative benchmarks and interviews with industry leaders, we dive deeper into the challenges presented in this blog and provide a four-step path to move forward.

Surviving in a commoditized tech market

A commoditized market is often perceived as an industry’s endpoint. A cycle of early innovation leads to the emergence of market victors, an influx of new competitors, and, finally, a standardized consensus regarding industry solutions, from pricing to value propositions to products themselves. Characterized by stagnant growth and decreasing corporate profit margins, commoditized markets frequently result in reduced long-term growth investment and a prevailing ‘play it safe’ mentality. This includes commoditized tech markets.

Of late, the intertwining of market globalization and technological innovation has accelerated the journey toward commoditization in most industries. A striking illustration of this trend is a recent Innosight analysis indicating that the average lifespan of an S&P 500 company has decreased by about ten years since the 1970s. Competitive disruption, the proliferation of marketplace platforms, and the ease of access to information have conspired to make enduring success an elusive goal. While these trends have manifested themselves across diverse industries and market types, the consumer technology sector is often susceptible (broadly referencing consumer-focused devices/wearables, software/video games, etc.).

The Acceleration of Commoditization in Today’s Markets

Let’s take flat-screen TVs, for instance. The price compression seen in this market over the last decade is indicative of the commoditization phenomenon. With Consumer Price Index data from the U.S. Bureau of Labor Statistics, you’ll find that the annual CPI-based price inflation for TVs since 1950 in which the average rate has been -6.5% per year, and much more over the last 2 decades (with a recent trend change/adjustment during COVID years).

As technology rapidly advanced (and standardized), the production costs decreased, and competitors flooded the market, the end result has been downward pressure on prices (a fantastic result for consumers!). The technical aspects of different models have become less obvious to most consumers, and price has become the primary differentiating factor.

4 Strategies for Consistent Growth in a Commoditized Tech Market

Fundamentally, the potential market opportunity with consumers drives rapid innovation and competition. Differentiating and standing out from the crowd requires a consistent focus beyond short-term results. Four broad strategies exist for consumer tech companies to consistently grow share and revenue, though only one (the final listed below) exists directly within the domain of commercial organizations.

  1. Continue Product Innovation
    For most consumer tech markets, the competition increasingly comes from upstarts and from tangential categories. Product innovation is a must to ensure as certain markets become saturated, you are positioned to move into the next.
  2. Build Stronger Integrations with Solution Network Effects
    Connectedness drives the need for products to exist within broader ecosystems (whether company-specific or broader). Finding positive externality flywheels within these ecosystems can help lower acquisition costs and differentiate from companies that neglect them.
  3. Enhance Customer Experience
    Particularly for lower-priced consumer technology where switching or updating to the latest and greatest happens frequently, ensuring a post-purchase experience that is unrivaled in market can lead to successful revenue retention.
  4. Focus on Branding and Upper Funnel Marketing
    With the ability to influence and differentiate at the point of demand capture or sale diminished, consumer tech companies can enhance how they engage before the purchase cycles begin to have a subconscious leg-up when decision time comes.

The Significance of Upper Funnel Marketing in D2C Sales

For consumer technology companies that have shifted or increased their focus on direct-to-consumer (D2C) sales, the fourth strategy is of particular relevance. Many of these organizations have over-rotated towards demand capture marketing strategies such as search engine optimization, pay-per-click advertising, and targeted social media campaigns. This over-rotation has largely occurred because of the direct attribution that predominates; if a sale happens after a paid social click, it gets attributed directly. While these tactics are critical for capturing in-market buyers, they typically fail to create meaningful differentiation or foster brand loyalty as they operate on more short-term, rational decision-making like pricing or discounts.

This brings us to the crux of the matter: the need to invest more in the upper funnel of marketing strategies. It’s about shifting some focus back to awareness and demand creation. In other words, before winning the consumer’s dollars, businesses must first put themselves in a differentiated position.

Establishing emotional connections with potential customers is crucial in this regard. Emotional branding transcends the mundane considerations of features and price points to tap into the consumers’ aspirations, needs, and lifestyles. When brands succeed in doing so, they increase the likelihood that consumers will gravitate towards their product when they’re in the market, even in a commoditized market.

Going Beyond Product Differentiation in a Commoditized Tech Market

Indeed, differentiation in a commoditized tech market is not just about standing out. It’s about resonating with the consumers on a level that goes beyond the product itself. As the consumer technology market continues to evolve and commoditize, it’s those brands that understand and implement this concept that will truly differentiate themselves from the rest.

Only 35% of tech CROs and executives are very satisfied with partner performance

BETHESDA, Md., January 25, 2023 – As technology businesses increasingly rely on channel partners to cover market opportunities, sell solutions, and deliver value-add services to customers, Marketbridge’s new report shows that only 35% of Chief Revenue Officers (CROs) and executives are very satisfied with partner performance heading into 2023. The report, “A CRO’s Guide to Transforming the Channel for XaaS Success,” highlights the challenges and priorities in the channel as vendors push to develop and sell new as-a-service (XaaS) solutions in the face of an economic slowdown.

The shift to a subscription economy presents major go-to-market challenges for vendors. Technology vendors must upskill partners on new delivery models, recruit the best XaaS-ready partners, and convert brand-new buyer personas, all while enabling partners to deliver recurring business outcomes. The report’s findings, based on both quantitative benchmarks and interviews with industry leaders, provide a clear path forward for CROs to transform their partner channels for XaaS success.

According to the report, modern partners (MSPs, CSPs, SIs, ISVs) are two times more likely to ‘significantly increase’ XaaS revenues in the next five years. However, only 35% of respondents on average were ‘very satisfied’ with partner performance outside of initial opportunity identification. Executives were also three times more likely than managers to believe they are behind the competition in quantifying the right number and mix of partners to deliver target revenues.

Mike Kelleher, Senior Vice President of Marketbridge’s Technology Practice, said, “The channel is at a critical juncture. CROs must take a holistic view of their partners and focus on developing a modern, sustainable model that leverages the right mix of partners to drive growth in the subscription economy. This report provides a framework for partner transformation in 2023 and beyond.”

Access the report here.

A CRO’s guide to transforming the channel for XaaS success

A CRO’s guide to transforming the channel for XaaS success

Research and insights on optimizing channel strategy to outperform the competition

In facing an uncertain economic climate ahead, technology businesses are rethinking already complex routes-to-market and partner channels. Coupling uncertainty with the rapid progression to XaaS selling models, CROs are faced with a burning question,“How do I transform and future-proof my partner channels to drive efficient revenue growth in the subscription economy?”

Our analysis

In conducting both quantitative benchmarks and interviews with today’s fastest-growing technology leaders, we set out to highlight the challenges and priorities in 2023 and beyond. In addition, we present a clear path forward for CROs to transform their partner channels for XaaS success.

This report covers

  • The need for change accelerated by the uncertain economic climate
  • The value pivot occurring in the channel
  • Direct-from-the-source challenges and priorities heard from tech executives
  • Four steps to building a modern partner model

Select insights

  • Modern partners (MSPs, CSPs, SIs, ISVs) are 2X more likely to ‘Significantly Increase’ XaaS revenues in the next 5 years
  • Only 35% of respondents on average were ‘very satisfied’ with partner performance outside of initial opportunity identification
  • Executives are 3X more likely than managers to believe they are behind the competition in quantifying the right number/mix of partners to deliver target revenues

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