Sendability score for DTC outreach? thoughts?

isa-ecom

I'm working on a feature for a customer research tool and could use some real-world input. We all know the pain of firing off an email or SMS to a lead with nothing but 'Hey, we exist' - useless. So I built a "sendability" score (1-100) that rates how strong your hook is and whether it actually ties into what you're selling.

The idea is simple: you pull in recent activity, abandoners, repeat buyers - then the tool scores them so you know exactly who deserves a custom opener. If there's no good data, the score tanks.

But here's where I'm stuck. What do you actually look for in a DTC lead before you reach out? Is it recency? A clear signal like "added to cart but didn't check out"? Or something else? And how do you craft an opener that doesn't feel like boilerplate but actually converts?

A colleague mentioned they score higher on people with a recent unboxing post or a support ticket about sizing - that's golden. But scraping that kind of nuance into an automated score is tricky.

Would love to know what makes you hit "send" vs. skip. Not looking for generic personalisation - I want the profit-driven trigger.

communityfirst

love this approach - scoring leads based on recent activity and a clear pain point is exactly how we turn visibility into real action. timing with relevance always outperforms blanket personalisation. Feels like a smart team win when the data lines up so beautifully

masoncollab

Totally agree on the sendability score concept. From my side working with creators and negotiating collabs, I'd prioritise recent activity and job changes over perfect personalisation every time. People respond to urgency and relevance way more than a clever opening line - it's about what's actually happening in their world, not how slick your hook is.

cpaoptimizer

I get the concept, but naming it "Sendability" might confuse people with deliverability scoring. What you're really measuring is opener quality - how compelling the hook is. Something like "Opener Strength" or "Reason-to-Reach Score" would be clearer.

For a solid opener, I look for three signals: a recent trigger (hiring, product launch, complaint post), a clear reason why it matters to them, and a natural bridge to what we do. Not just "saw your LinkedIn post," but "saw you're expanding the sales team - here's how we helped similar groups shorten ramp time."

Weak signals to avoid: generic job titles, stale funding news, or scraped "congrats on growth" - everyone sees through that. Strong signals: recent tool switches, public pain points, new campaigns, pricing pressures, or anything they've said in the last 30-90 days.

Separating the score into two parts would make it far more useful: "hook strength" for the opener quality, and "send risk" for deliverability signals (bounce rates, domain reputation, list hygiene). We work on SMTPProvider, and from our side a perfect opener still lands in spam if the list is messy. If you can feed delivery data back into the score later, the feature becomes genuinely actionable - not just AI judging copy.

wordweaver

Oh, honey. "Sendability"? that's not a feature, that's the bare-minimum entry ticket. apollo and Hunter have been doing this since my gran was on Facebook. before you sink dev time into it, ask yourself: would someone actually jump ship to your platform just for this? If the answer isn't a resounding "hell yes" (and it won't be), you're building a table-stakes solution nobody asked for

datanerd

Sendability has been an absolute workhorse for me over the last five years - I'd argue it's essential rather than just nice-to-have. The logic behind pre-flight checks for deliverability saves so much headache down the line, especially when you're juggling enterprise ABM sequences where every touchpoint counts. Curious how you're handling bounce thresholds and domain reputation scoring under the hood

isa-ecom

honestly, it depends how granular you want to get. I base it on persona + behavioural triggers rather than just demographics. For example, a first-time buyer's pain point is usually "Is this legit?" - so sendability there means trust signals and delivery timing. A repeat buyer's pain is "I want this before I run out" - so it's about replenishment cadence and loyalty loop nudges.

Are you mapping pain points against specific lifecycle stages or just lumping everyone into one bucket? That's where I've seen most sendability tools fall apart - they treat "abandoned cart" the same for a browser and a VIP customer.

funnelhacker

Exactly. "Timing with relevance" is what separates emails that get replies from crap that gets binned. Dropping some surface-level personalisation from Instagram is a waste of budget.

If you're scoring sendability, I'd be weighting signals that actually predict intent:

Recent role change or promotion → decision-maker, open to new workflows.
They're hiring for a function your product replaces or supports → clear pain point and allocated budget.
They just posted or commented about a problem your thing solves → active search for solutions. That's your hook with zero friction.

Then the opener writes itself. "Saw you're hiring X / rolling out Y, curious how you're handling Z" outperforms any "loved your post about leadership" fluff every time. Purely because the first signals intent, the second signals noise. Measure reply rates and you'll see the gap.

isa-ecom

Right now my pipeline runs on this:

Employment check (your internal data vs their LinkedIn - that's zero points if mismatched)
Recency (only pull posts from the last two months - 35 points)
Connect each post to a solution you offer, the output is a "hook." That's 35-70 points, AI discretionary
A judging process picks the most coherent hook - 70-100 points, also AI discretionary

Anywhere in that chain it can fail. You might get only 40 points because the lead had recent posts but none relevant to your product. They're still worth chasing, just not as strongly.

It's mad - on my lists about a third of the data set falls through. That's a lot of potential spend left on the table if you're not filtering for actual intent.

masoncollab

that breakdown makes sense - the weighting sounds well thought out. On the lower-scoring third, I'd flag them separately instead of burying them in the sort. when I'm sourcing UGC, those creators often have killer engagement despite smaller followings. a simple tag keeps them in the pipeline without messing up the sort order. happy to chat more about creator scoring if you're interested

wordweaver

right, that's a much clearer pitch. Apollo finds the bodies, Pitchsmart reads the room - different beast entirely. if it gets legs, give me a shout.