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📊 Featured Benchmark Data (from Benchmark Groups)
We close X deals/month. Is that good?
Is our traffic below average?
Is our Cost Per Click higher than competitors?
Benchmarks help answer these questions. They let you see where you’re ahead of the curve, and where there’s room to improve.
Data like this used to be hard to get. Companies would spend hundreds of thousands to see how they stack up to their peers.
Not anymore.
Now you can answer questions like this anytime, with our new Benchmarks Explorer tool.
Just search for the metric or integration you need, and browse hundreds of Sales, Marketing, Revenue and CS benchmarks.
You can even build a custom Benchmark Report with the numbers you care about, and get email updates as they change every month.
Oh, and it’s totally free – you don’t even need an account to use it.
We worked hard to make it as valuable as possible, so if you do give it a try, then hit “reply” and let me know what you think! We’d love your feedback or suggestions on how we can improve it.
💡 Trends & Insights (from Reports & Surveys)
If you had to recommend one or two social platforms for a B2B company to test for their demand gen program, you probably would’ve picked LinkedIn, Facebook, or Instagram.
So would I. But then I saw something surprising in our benchmark data 👀:
The median value of TikTok’s Cost Per Click in July 2023, was $0.39. You read that right, thirty-nine cents. And for B2B companies in August 2023, it was just $0.41.
That same data says that LinkedIn or Instagram would easily cost $3-5/click for B2B. So if you’re running brand awareness or impression-based ads on LinkedIn as part of your demand gen program, maybe it’s time to give TikTok a try.
To learn more, our team surveyed 35 B2B marketers to learn more about how they use TikTok ads. By the time you get done reading, you might want to try them yourself.
Here are some of the insights:
📈 Drive Predictable Performance (from Metrics & Chill)
Blake Strozyk has worked with dozens of B2B companies, including Refine Labs, and shared the 3-stage framework he uses to help clients build efficient paid programs at Bull Media.
There was a lot here, so here’s my stab at a summary:
Stage 1) Identify your foundations
Evaluate if you’re ready for a paid program yet, who exactly you’re targeting, and what you’re willing to pay in the first year to acquire them.
Whether or not you can scale a paid program will depend on a variety of factors, including your category maturity, company maturity, ACV, TAM, etc. So the goal is to agree on what you’re willing to pay to acquire someone and form a hypothesis of who you’ll be reaching, on what channels, and with what messaging.
Sounds elementary, but a lot of companies don’t get this right.
Stage 2) Go from 0 to 1
The goal here is to test your hypothesis and look for early signals that this will be a successful program. Part of this is setting expectations. Many companies kill experiments in 90 days, which isn’t enough time to gauge effectiveness for many larger sales-led organizations.
What’s the “1” you’re getting to? Leading indicators that this will drive revenue. What they are depends on the company.
If you have a high-velocity sales cycle or are a product-led growth company, you might look to see closed/won deals or signups in the first 30 days.
If you’re an enterprise company with a 6-month sales cycle, early signals of success might be increased demo bookings or your outreach team reporting increased responsiveness, as prospects become more familiar with who you are and what you do.
In general, you’re measuring overall inbound volume, deals attributed to your ad program, and down-funnel performance.
Stage 3) Scale from 1 to 100
Your goal here is to get consistent pipeline at the most acceptable cost while continuing to refine, improve, and scale your paid program.
In Stage 2, you validated your hypothesis. You got early signals your paid program would help you acquire customers at the price you agreed upon.
In Stage 3, it’s time to get as much out of it as possible. You want to know you can predictably drive $x in pipeline and begin scaling it.
Maybe you saw success with case studies run to 1 vertical, so you begin to run case study ads to the rest of the verticals you target. Whatever it may be, you’re doing more of what’s working, testing new things that may work better, and expanding deeper into your market or broader into other verticals.
It was such a great chat, that summary doesn’t do it justice. Blake also touched on what needs to be in place *before* testing paid programs, tips for running paid on various channels, and how social ads compound over time.
Check out the full interview to hear all of Blake’s insights…
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