Steffen Hedebrandt, co-founder and CMO of Dreamdata, is helping B2B SaaS companies with their marketing attribution. He takes a competitive approach to his work and likes to "win". In this context, a good way to win is to understand your customers’ activities and path as you sell to them:
"If there are things that you see consistently present when you sell to a customer, then you can go back and repeat the things that are working. You can probably also stop the activities that are not working."
As a marketer, Steffen is trying to produce revenue with his marketing activities, and understanding this attribution — what works and what doesn't during the customer journey — is vital. Over time, the team at Dreamdata has defined its customers as B2B SaaS companies, and they serve them with a go-to-market data platform that captures digital touchpoints on a broad scale. Data that previously was scattered across many tools can now be combined to get deeper customer insights.
Steffen's co-founders come from Trustpilot and they wanted to better understand their customers' journeys. Steffen wanted a better way to analyze his ad spend and its impact on revenue. When the three joined to create Dreamdata, they were able to create a prototype that achieved these goals and would solve real pain for B2B SaaS companies.
Assigning better attribution
Jane asks about the common challenges that SaaS companies face, and the mistakes that they make when it comes to attribution. According to Dreamdata's recent benchmark study, the first thing is lacking awareness of how long the customer journey can be:
"We looked at 500 customers and the average journey there from the first touch to winning a deal was 192 days. An average of 32 sessions were involved in that deal."
The issue with some of the traditional tools, and why this may seem like a surprising number of interactions, is that they rarely accurately follow a customer across different customer sessions, devices, etc. For instance, you may attribute a customer finding you to organic or direct search, when in reality they are simply returning to your brand after seeing a paid ad multiple "touches" earlier in their journey. At a high level, Dreamdata differs from other analytics because they can assign visitors anonymous IDs from the very first interactions they take. When they hit a point in their journey when they choose to identify themselves, booking a demo or downloading an ebook, for example, they provide consent to link their identifying information to any previously anonymous touchpoints:
"As soon as we can resolve your identity with the account, all those touches go into the accounts timeline."
And their algorithms work as a customer data platform so that they can figure out users across multiple devices:
"Say you converted on your phone the first time. Then we start sending your emails which you then click from your computer. Now we know that we shipped the email to this person on the phone, but it got clicked from a computer. Now we know that when one of these two devices is on the website, it's this same person."
Steffen says that while there is some complexity in having 32 average touches to conversion in this space, it can also be helpful for attribution. If you aren't able to track one of the interactions, there are still many other interactions or chances to identify how a user is becoming a customer.
Some attribution is difficult
Jane asks how to track more notoriously difficult marketing initiatives like podcasting. Beyond promocodes and landing pages, are there other things that can be done? Steffen says:
"You should do marketing that makes sense. We make a product for SaaS companies. You have a podcast for SaaS companies. Hence, if I spent my time on this marketing show, it's still the right people who are listening. So you should join data together with common sense or gut feeling."
He admits that while there are things that just can't be measured well, you shouldn't let that stop you from trying. While self-reported data from your customers isn't usually super valuable, Steffen thinks it still may be worth trying to collect:
"For all content you do, you need to try to describe the value on a qualitative level. If somebody shares the podcast on social media, take a screenshot. If you see somebody commenting, 'You should listen to this podcast', take a screenshot. If you anecdotally hear somebody speaking about your podcast at a conference, you should tell your team about it."
It's all about finding and sharing anecdotes to strengthen the "gut feeling" instincts. They don't necessarily have to come from a web form, either. Steffen found that the friction of self-reporting wasn't worth it for Dreamdata given how vague the answers were, but Jane shares that she asks a few questions live when hosting Userlist demo calls with prospects. Those answers are helpful in understanding the email landscape.
Marketing channels, customer journeys, and experimentation
In contrast to podcasting, which is more difficult to attribute, Steffen says that it's relatively easy to understand leads that are actively searching for the solution. It's easy because these people are so close to booking a demo or signing up for your product. They could come from Google search, organic search or paid ads. They could come from review platforms or SaaS marketplaces. The difficult part is that potentially only 2% of your market is actively buying at any given moment:
"This is where you need to do marketing tactics to get in front of the right people that are just not in the market right now, so that when they switch to buying, you can capture that demand, maybe even without competition, because you've done your marketing well before that."
Knowing that many B2Bs heavily underestimate how long their customer journeys are, Steffen recommends that companies start storing all the data about the journeys in one place. By digitizing the behaviors now, you will have that data later when you go running different marketing experiments. Timing the length of these experiments can be difficult depending on how long the customer journeys are — it may be impractical to wait as long as needed to see if deals close. To get around this, Steffen encourages finding a good proxy for revenue that isn't necessarily a fully closed deal:
"Anybody involved in revenue should know these numbers in your company: for a deal, how many opportunities do you need? For an opportunity how many marketing qualified leads do you need? For a marketing qualified lead, you need X amount of leads. And if you know these metrics, then you have a qualified guess about what activity leads to revenue."
For smaller companies that may not have the amount of data they need for rigorous quantitative analyses, it is important to collect the data today. That way it will be available for analysis tomorrow.
Funnels, awareness, knowledge transfer
Jane asks Steffen how he juggles different marketing funnels. While he has automations set up at Dreamdata, he doesn't like to think about funnels in the typical sense because it's hard to force users into a set path. Instead, he says:
"I think it's about consistently producing high-quality content and getting in front of people. You're consistently staying top of mind with quality inputs to their world."
At Dreamdata, they do this with "social selling" so that they can get a log of high-quality touches in before conversion. To find these leads, he says go to where your customers are expressing their most clear intent to buy. For Dreamdata, that might be finding the people that are already on G2 looking for attribution. As their sales teams learn from the selling process, similar sentiments that they hear over and over get distributed to the marketing team, so that the information doesn't get lost and can be used to make process improvements.
Final advice
Do try to know as much as you can from the data.
“You want to support your thinking and your gut feeling with data so you get more insights into whether the ads are working or not.”
Don't blindly trust any of the data that you are looking at.
“If something looks too good to be true, it's always too good to be true.”
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