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How did you change up your stack? Take the 2022 MarTech Replacement Survey

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How did you change up your stack? Take the 2022 MarTech Replacement Survey

When we analyzed the results from the 2021 MarTech Replacement Survey we found marketers and marketing technologists trying to square the circle. Budgets were tighter, but you were still in the market for better features, especially as you coped with the surge of digital engagement prompted by the widespread lockdowns of the preceding months.

Cost wasn’t the primary driver. Budget was an important factor, but it wasn’t the ultimate driver of replacement decisions. Whether homegrown or commercial applications were being replaced, features trumped cost. In each case, more than 50% said the replacement was driven by better features, although around 41% did cite cost as the reason for migrating solutions. 

Two closely associated factors were cited in the quest for stack improvements. Better data centralization and data capabilities were number one on your wishlist, while being able to deliver an improved customer experience was in second place — and of course data and CX go hand-in-hand.


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What’s changed? As we look back over the last year, we’ve come a long way. Real life is largely back, along with in-person shopping and business and vacation travel. Customers are still in digital channels — that trend isn’t changing — but you can also reach them out-of-home again, and they’re on the move.

How has that impacted your marketing tech stack decisions? Have you changed course or are you still on the pre-pandemic digital engagement journey that accelerated so much in 2020 and 2021?

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Please complete the survey. We want to hear from you, the MarTech community, about the stack decisions you’ve been making. Have you replaced any solutions in your tech stack in the past year? Have you moved from homegrown legacy applications to commercial solutions (or vice versa)? And what impact have those changes had on your team?

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The 2022 MarTech Replacement Survey takes about three minutes to complete, and the results will help us all, as a community, to understand the major stack trends.


About The Author

Kim Davis is the Editorial Director of MarTech. Born in London, but a New Yorker for over two decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, digital- ad data-driven urban planning, and applications of SaaS, digital technology, and data in the marketing space. He first wrote about marketing technology as editor of Haymarket’s The Hub, a dedicated marketing tech website, which subsequently became a channel on the established direct marketing brand DMN. Kim joined DMN proper in 2016, as a senior editor, becoming Executive Editor, then Editor-in-Chief a position he held until January 2020. Prior to working in tech journalism, Kim was Associate Editor at a New York Times hyper-local news site, The Local: East Village, and has previously worked as an editor of an academic publication, and as a music journalist. He has written hundreds of New York restaurant reviews for a personal blog, and has been an occasional guest contributor to Eater.

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B2B customer journeys that begin at review sites are significantly shorter

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B2B customer journeys that begin at review sites are significantly shorter

The B2B customer journey can be a long one, especially when the purchase of expensive software subscriptions is under consideration.

“The average B2B customer journey takes 192 days from anonymous first touch to won,” according to Dreamdata in their 2022 B2B Go-to-Market Benchmarks — a statistic described by co-founder and CMO Steffen Hedebrandt as “alarming.”

But the report also indicates that this journey can be significantly sped up — by as much as 63% — if accounts begin their research at software review sites, gathering information and opinions from their peers. Journeys that originate at a review site often lead to deals of higher value too.

Fragmented data on the customer journey. Dreamdata is a B2B go-to-market platform. In any B2B company, explained Hedebrandt, there are typically 10 or even 20 data silos that contain fragments of the customer journey. Website visits, white paper downloads, social media interactions, webinar or meeting attendance, demos, and of course intent data from review site visits — this data doesn’t typically sit in one place within an organization.

“We built an account-based data model because we believe that there’s such a thing as an account journey and not an individual journey,” said Hedebrandt. “So if there are two, three or five people representing an account, which is typically what you see in B2B, all of these touches get mapped into the same timeline.”

Among those many touches is the intent data sourced from software review site G2. Dreamdata has an integration with G2 and a G2 dashboard allowing visualization of G2-generated intent data. This includes filtering prospects who are early in their journey, who have not yet discovered the customer’s product, or who have discovered it but are still searching. This creates a basis for attributing pipelines, conversions and revenue to the activity.

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“Strategically, our ideal customer profile is a B2B software-as-a-service company,” said Hedenbrandt. “B2B SaaS companies are particularly ripe for understanding this digital customer journey; their main investment is in digital marketing, they have a salesforce that use software tools to do this inside sales model; and they also deliver their product digitally as well.” What’s more, it takes twice as long to close SaaS deal as it does to close deals with B2B commercial and professional services companies.

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Read next: A look at the tech review space

The Benchmarks findings. The conclusions of the 2022 Benchmarks report is based on aggregated, anonymized data from more than 400 Dreamdata user accounts. Focusing on first-touch attribution (from their multi-touch model), Dreamdata found that customer journeys where a review site is the first touch are 63% shorter than the average. In contrast, where the first touch channel is social, the journey is much longer than average (217%); it’s the same when paid media is the first touch (155%).

As the Benchmarks report suggests, this may well mean that social is targeting prospects that are just not in-market. It makes sense that activity on a review site is a better predictor of intent.

Hedenbrandt underlines the importance of treating the specific figures with caution. “It’s not complete science what we’ve done,” he admits, “but it’s real data from 400 accounts, so it’s not going to be completely off. You can only spend your time once, and at least from what we can see here it’s better to spend your time collecting reviews than writing another Facebook update.”

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While Dreamdata highlights use of G2, Hedenbrandt readily concedes that competitor software review sites might reasonably be expected to show similar effects. “Definitely I would expect it to be similar.”

Why we care. It’s not news that B2B buyers researching software purchases use review sites and that those sites gather and trade in the intent data generated. Software vendors encourage users to post reviews. There has been a general assumption that a large number of hopefully positive reviews is a good thing to have.


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What Dreamdata’s findings indicate is that the effect of review sites on the buyer journey — especially as the first-touch channel — can be quantified and a value placed on it. “None of us questioned the value of reviews, but during this process you can actually map it into a customer journey where you can see the journey started from G2, then flowed into sales meetings, website visits, ads, etc. Then we can also join the deal value to the intent that started from G2.”

Likely, this is also another example of B2B learning from B2C. People looking at high consideration B2C purchases are now accustomed to seeking advice both from friends and from online reviews. The same goes for SaaS purchases, Hedenbrandt suggests: “More people are turning to sites like G2 to understand whether this is a trustworthy vendor or not. The more expensive it is, the more validation you want to see.”


About The Author

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Kim Davis is the Editorial Director of MarTech. Born in London, but a New Yorker for over two decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, digital- ad data-driven urban planning, and applications of SaaS, digital technology, and data in the marketing space.

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He first wrote about marketing technology as editor of Haymarket’s The Hub, a dedicated marketing tech website, which subsequently became a channel on the established direct marketing brand DMN. Kim joined DMN proper in 2016, as a senior editor, becoming Executive Editor, then Editor-in-Chief a position he held until January 2020.

Prior to working in tech journalism, Kim was Associate Editor at a New York Times hyper-local news site, The Local: East Village, and has previously worked as an editor of an academic publication, and as a music journalist. He has written hundreds of New York restaurant reviews for a personal blog, and has been an occasional guest contributor to Eater.

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