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Foreword: Pradyut is Head of Product Marketing & Analyst Relations at Akinon, a leading composable digital commerce platform. He is also a veteran Martech practitioner whose unique insights on marketing & personalisation come from over a decade of product marketing leadership at Insider, Netcore, and Clevertap.
Roheet and Sreelesh met Pradyut in September 2024 as they sought feedback for Zenie AI at the time of launch. Their conversations reignited shared thoughts and beliefs on how marketing teams today have a plethora of tools to work with, but find it more difficult to personalize experiences for the customer. Pradyut wears his Practitioner and Analyst hat on as he shares a walk down the history of marketing automation. As the adage goes, "You can’t know where you’re going until you know where you’ve been"!
Over 84 months of having a front-row seat to the marketing technology or “martech” battle royale has taught me a thing or three. The collective industry has borne witness to a dramatic growth story; often painted in paradoxical hues. The leap from simple automation and campaign management to integrated, intuitive segment-of-one hyper-personalization has been generational. But, standalone tools with table-stakes functionalities continue to package traditional customer engagement remedies in AI-embellished wrappers or remain consciously impervious to rapidly evolving market realities that demand a sterner look at archaic product roadmaps.
Legacy vendors and first-mover shakers continue to strike a balance between relevance and revenue. While disruptive up-and-comers and late-movers are carving out differentiated niches for themselves on the back of genuinely innovative product and go-to-market (GTM) strategies.
There’s been enough space for macro and micro-category growth across the spectrum in the last couple of decades - from companies that offer a whole host of solutions across the AARRR Pirate Funnel to tools that cater to specialized industry-specific use cases and an entire universe of modularized technologies that promise the promised land in between.
The cycles of emergence, stagnance, re-emergence, and scalability of core martech solutions - CRM systems, Identity Resolution and Customer Data Platforms, Customer Journey Orchestration, Multi-Channel, and Email Marketing Hubs, Content Management, Digital Asset Management, and Digital Experience Platforms, SEO, Social Media Marketing, and Marketing Performance Measurement systems, and more - have served to shape latent and authentic demand-supply dynamics. As well as periods of oscillation between best-of-breed martech stack fragmentation and consolidation.
For an industry practitioner and a business buyer, a lot of this is akin to drinking straight from a firehose. Especially in terms of keeping pace with the changing landscape and aligning vendor evaluation to critical business objectives. So, let me attempt to simplify this entropic evolutionary martech growth story and trace its journey across the ages.
Join me on this nostalgia trip, will you?
According to David Raab, a pioneer in this space and the Godfather of Customer Data Platforms (CDPs), this story has largely been scripted on three fundamental pillars:
- Marketing channels
- Tools adopted by marketers to manage engagement across those channels, and
- The quantum and quality of data accessible to marketers to enable engagement
In his Marketing Technology Timeline, he summarises this journey across key eras up until 2010. He also underpins the fact that “marketing technology and using data to enhance campaign performance didn’t emerge in any significant way until computers were applied to list management in the 1970s. And, expanded rapidly with the adoption of the internet in the 1990s and 2000s.”
Note: The yellow highlights depict the volume of technology available during each period.
In essence, the proliferation of tools has a direct correlation to the technology breakthroughs that came thick and fast during the computer and internet eras. Breakthroughs that also had a chronicled trickle-down effect on the number of touchpoints and unique data-points critical to engagement (and retention) across a customers’ lifecycle.
It was also in the 1980s that direct database marketing; a precursor to contemporary CRM systems, took shape. The early contributions of Robert and Kate Kestnbaum in popularizing the use of statistical methods in gathering and analyzing customer data cannot be understated. The gospel-like concepts about customer data, behavioral segmentation, channel management, CLTV, and more gradually became part of marketing parlance and strategy.
The entire Customer Relationship Management (CRM) movement received a shot in the arm with the founding of ACT! (Automated Contact Tracking) in 1987. Often regarded as the first mainstream CRM and contact management system, ACT! came as a blessing to many small and mid-sized businesses that were pivoting to off-the-shelf standalone sales automation software.
The CRM revolution gathered further momentum with the founding and scaling of Siebel Systems in 1993. Having initially built their business around sales force automation, they soon extended their application suite to encompass CRM software. A runaway hit in a market that was rapidly seeing new pretenders hit the shelves with minor product and price differentiation, Siebel accounted for almost 45% of the CRM market by 2002. A reality that prompted Oracle to acquire them for $5.8 billion in 2005; to reignite their concerted foray into the CRM and customer experience domain.
Software companies like GoldMine also offered strong CRM alternatives as part of their product portfolio; as competition scaled new levels with legacy players taking cognizance of new business requirements.
There was another major development during this period. A development that initially appeared as an almost-negligible blip on the industry radar. In 1999, Salesforce debuted its CRM product packaged for the first time as SaaS (Software-as-a-Service). It marked a seminal shift in how this space - and marketing technology, in general - was making the transition to the cloud.
The Dotcom Bubble Burst in 2000 emboldened established players like Oracle, SAP, PeopleSoft, and more from doubling-down in this direction; extending their existing Enterprise Resource Planning (ERP) products with basic CRM capabilities.
This period is also underpinned by the rise and adoption of bulk email marketing. The likes of Constant Contact (founded in 1995) and Mailchimp (founded in 2001) sowed the initial seeds of basic email marketing automation with capabilities that were definitely pathbreaking for that time. This established their credibility as “Innovators” and “Early Adopters” when looking at it through the prism of the Law of Diffusion of Innovations.
In the same vein, bulk short message service (SMS) marketing also started gaining a stronghold as a channel of mass and low-grade segmented engagement as mobile networks and devices started proliferating across mature and emerging markets. This was a channel largely restricted to pockets of Europe and Asia; and a harbinger of modern-day mobile marketing as we know it.
As businesses - both established and emerging - took baby steps towards digital channels of customer acquisition and engagement, these early tools offered them the ability to craft, send, track, and measure email and SMS campaigns. One small step for marketing technology, one giant leap for targeted personalization.
As the CRM movement took centre-stage and an increasing number of vendors entered the fray, businesses were soon spoilt for choice. Rapid migration to the cloud also produced a knock-on price reduction effect; positively impacting accessibility and scalability. Founded in 2004; open-source, cloud-based applications like SugarCRM manifested into a welcome boon for many small and mid-size businesses looking to implement an affordable and reliable solution. A solution that brought increased integration capabilities, flexibility, and customizability collectively to the table.
India’s bold entry into this space was flagged by Zoho’s (founded in 1996) standalone CRM product in 2005. Rudimentary for its time - sure. But, momentous for its functional evolution and business impact over the years.
And, the pivotal transitory moment towards modern-day, SaaS-led CRM systems came with the founding of HubSpot in 2006. Since then, they have been one of the pioneers in crafting frictionless customer experiences built on the foundation of inbound marketing and an integrated suite of products.
But, let’s not view the hullabaloo around CRMs in isolation, shall we? As businesses acknowledged and embraced the impact of content-rich web experiences; early Content Management Systems (CMS) like Drupal (founded in 2000), WordPress (founded in 2003), and SquareSpace (founded in 2003) established an early-mover advantage. They enabled non-technical marketers - with limited to no knowledge of HTML, CSS, or coding - to build, publish, manage, and scale web content.
The likes of Wix (founded in 2006) and Weebly (founded in 2006) only bolstered this martech sub-domain. These still-isolated platforms empowered businesses to deliver and elevate digital web browsing, consumption, and purchase experiences. With Shopify’s entry into the digital commerce space at around the same time; setting up eCommerce operations was further simplified. Integration and seamless operation with other value allied cloud-platforms like Email Marketing Hubs or CRMs was still a challenge.
This was merely the tip of the iceberg. Modern martech stacks began taking basic shape with the inclusion of web analytics tools. The likes of Omniture (that later became Adobe Analytics) and Google Analytics (re-packaged and launched in 2005 after Google’s acquisition of Urchin Software Corporation) were major game-changers in this context. They began enabling marketers to track, analyze, and optimize website traffic, customer behaviour, conversion rates, and more. The shift towards data-driven decisioning to amplify experiences across web and mobile was now (truly) underway. Albeit deep-tech integration to develop a 360-degree customer profile was still a million-dollar challenge waiting to be tackled.
The result? A burgeoning quantum of quality customer data-points that sat in silos with limited accessibility or utility. The consequent result? Deeper personalization was still a fair far-cry away.
The mainstream launch and adoption of both iOS and Android-powered smartphones in 2007 paved the way for contemporary mobile marketing channels such as push notifications, in-app messages, and SMS. While this was still new, largely uncharted territory for digital businesses that were aligning their fates to a morphing mobile-first world, these developments set in motion the demand for multi-channel marketing automation platforms capable of acing the 4Rs. i.e. delivering the right message to the right customer through the right channel, at the right time.
These technological breakthroughs also dovetailed with the early usage of geolocation-based targeting and beacon marketing. An important step towards real-time marketing that eventually became a staple function of such platforms in the long-run.
Vendors like Pardot, Marketo, and HubSpot continued to revolutionize the multi-channel marketing automation space as customer touchpoints rapidly expanded in an increasingly phygital environment. The agility, flexibility, relative ease-of-use, and healthy revenue run-rates of these players can be underscored by the fact that Pardot was acquired by Salesforce in 2013 and Marketo by Adobe in 2018. A strong signal to the collective market that the heavyweights were (and remain) in no mood to sacrifice market share in a fragmented landscape.
Even today, their all-in-one and one-for-all platforms may have a dated UX and functionality veneer. There are still enough buyers that consider them actively based on their brand legacies and proven track records. Especially in high-ticket markets like North America, Western Europe, and increasingly the Middle East.
The emphasis on accurately mapping and responding to unique customer journeys across their lifecycle necessitated the growth of Customer Journey Orchestration capabilities. The likes of Twilio, Bloomreach, Iterable, and Braze positioned and repositioned themselves with cross-channel engagement capabilities to further put the spotlight on this space.
Innovative vendors like Insider, CleverTap, MoEngage, and more adopted (and continue to adopt) differing growth paths to solving the same CLTV and retention maximization problem with varying segmentation and analytical functionalities Their early attempts at embedding an AI layer often involved the use of Machine Learning-led capabilities to optimize campaign subject lines, content, send times, predict churn, app uninstalls, propensity to abandon carts, purchase, and more.
Customer Data Platforms (CDPs) also made a stunning comeback into the marketing public’s consciousness. The challenge of consolidating incoherent, disconnected, fractured, and/or de-duplicating valuable data-points to develop a real-time understanding of every single customer - from being an anonymous visitor to a brand loyalist - was (and at many levels), still remains a major marketing hurdle. The likes of Treasure Data, Segment.io, Tealium, and more continue to solve for this.
Amazon’s skyrocketing sojourn to the top as an eCommerce marketplace of global standing also put the microscope on recommendation engines in this era. According to McKinsey, Amazon was generating as much as 35% of their revenue through personalized product recommendations and suggested bundles; as early as 2012. A staggering metric for that time that only underlined how historical and live behavioral and preference data like search, browsing, clicks, add-to-wishlist or cart actions, purchases, payment methods, delivery choices, and more could be leveraged to drive up in-moment conversions, average order values (AOV), and CLTV.
This spawned the growth of standalone recommender platforms like Dynamic Yield, Nosto, Qubit, Kibo Commerce, and more. These companies offered digital businesses across eCommerce, grocery, retail, media/OTT, electronics, telecom, BFSI, automotive, and more to add an additional layer of contextualized engagement via the power of collaborative, content-based, or hybrid filtering models best suited to their needs. Essentially leveraging the power of targeted recommendations to impact the metrics that matter the most (TMTMTM); like the “giants do”. McDonald’s purchase of Dynamic Yield for $300 million in 2019 was another confirmatory nod to the key role of such platforms in expediting digital transformation at the speed of light. Incidentally, Mastercard went on to acquire Dynamic Yield from McDonald’s in 2022.
This decade is also synonymous with the increased adoption and monetization via social media marketing tools. Platforms like Hootsuite, Buffer, Sprout Social, and more quickly became a vital weapon in most businesses' digital marketing armoury. They allowed marketers to create and schedule posts across multiple brand channels, drive engagement and conversions, understand audience preferences, and optimize performance. Social listening tools like Mention and Brandwatch further enabled businesses to track brand sentiment and conversations happening across the web. Coupled with platform-led audience retargeting and the power of ad networks; the seeds of social commerce were watered on the greener side of conversions and revenue.
With more data, comes greater marketing muscle. But, it also places a premium on data analytics and attribution to make better data-driven decisions. Tools like Google Data Studio, Tableau, Gainsight, and more started enabling marketers to create data-rich dashboards gleaned from multiple relevant sources. All with a focus on improving conversions and unlocking new revenue streams for businesses accounting for every invested marketing dollar.
And, then came another watershed moment in contextualized customer experiences; on a preferred customer channel. WhatsApp Business launched in 2018 and ignited the entire conversational commerce paradigm. It began as a simple interactive and largely chatbot-led channel for whitelisted businesses to share automated messages, updates, alerts, and more. A precursor for more personalized campaigns, interactive content, instantaneous customer support, and more.
Scott Brinker, VP of Platform Ecosystem at HubSpot and a pioneer in this space published The Marketing Technology Landscape in 2011. One of the most oft-cited sources of martech vendor growth across categories, its inaugural edition listed 150 solution providers. That number grew to 8,000 by 2020. Take a second to wrap your head around that.
So far, so great, right? Tools and platforms aplenty for every conceivable marketing use case. The promised land didn’t seem that fuzzy on the horizon. Or, did it? For that matter, does it?
The plethora of options available for evaluation and investment has only raised and exacerbated “that” age-old debate. Do businesses prefer a best-of-breed solution or want an integrated suite with critical capabilities? In fact, according to a Gartner survey across 2019 and 2020; there was a 30 point increase in marketing technology leaders outlining a preference for integrated suites over best-of-breed solutions. A telling statistic that only snowballed in significance. Especially in the future-forward context of the Pandemic, digital transformation mandates, straitjacketed budgets, and unpredictable customer behavior.
This signalled the pressing need to reduce martech stack complexity by enabling seamless integrations across products with the ability to activate more customer data with greater speed, scale, and security.
The magic of marketing technology lies in the productive marriage of creative human intelligence and machine-led tech capabilities. Fortified on the back of responsible customer data application. To spawn memorable and meaningful experiences that keep customers coming back for more.
The Pandemic of 2020, the advent of Generative AI, and deeper demand for hyper-personalized customer experiences has propelled the martech space into a completely different orbit. Or, galaxy; if you will. And, that alone merits a follow-up post to chronicle what has transpired since and what the crystal ball of future predictions prophecy.
Watch this space for more; as the martech battle royale moves into the 2020s and beyond.
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