Summary
An IT consulting company told MotiveGTM that its email system was broken, and its marketing team was celebrating out-of-office replies and double opens as wins. Our audit found sound targeting and a list that had barely heard of our client's company name. Six weeks of LinkedIn ads to that list, a rebuilt sending setup and matching storylines in the subject lines took the positive reply rate from zero to 7% within three months. The campaign cost $4,000 and produced $40,000 in booked revenue.
At a glance
- Client
- An IT consulting company
- The complaint
- An open rate of 1.7% and no positive replies, with out-of-office messages and double opens counted as wins
- What we did
- LinkedIn ads and retargeting to the email list, a rebuilt sending setup and matching storylines in subject lines
- Result
- A 7% positive reply rate after three months, with $40,000 in booked revenue and six meetings
The problem
The client, an IT consulting company, came to us saying that its email marketing system was broken. The client's rate of genuine, positive replies was zero. In this write-up, a positive reply is a reply from a person that shows genuine, positive intent, and it excludes out-of-office messages, unsubscribes and replies saying the person is not interested.
The setup also worked against the client in a way the reports did not show. The emails carried embedded tracking, and tracking pixels and links can lower the chance that a message is delivered, which defeats the purpose of measuring it.
The MotiveGTM approach
We began by auditing the email system from the targeting backward. That meant looking at who the client was sending to, including their profiles, designations, company profiles, geographies and technology stack, and at how well each of those matched the buyers the client had won before.
The audit found that the targeting was sound. The list was full of the right people at the right kinds of companies, which made fit an unlikely explanation for an open rate of 1.7%. Fit describes who should buy, and it says nothing about whether those people know the sender, want what it sells or are in the market this quarter. An email from an unfamiliar company asks for attention it has not yet earned, and the results suggest the recipients were not giving it.
That finding changed the question from how to fix the emails to how to make the sender familiar before the next email arrived. We recommended a six-week paid media campaign aimed at the list itself, with the email work running beside it.
The solution
The program had five parts, and the ads ran for six weeks.
- We ran LinkedIn ads to the email list. The campaign used single image ads that promoted a downloadable asset, and it ran against an audience of about 12,000 people at about 1,600 accounts. That gave them a reason to recognize the company before they met it in an inbox.
- We retargeted anyone who saw an ad once. One exposure rarely builds recall, which is why people who had seen an ad were shown it again.
- We moved people who clicked and downloaded into a separate nurture system. Anyone who engaged with an ad and downloaded the asset was followed up outside the email program, which kept the warmest people from receiving the same sequence as everyone else.
- We rebuilt the email infrastructure at the same time. The client bought new mailboxes and sent from different domains, and we used a separate mailbox strategy for Microsoft mailboxes. The same effort covered list and data hygiene. We also removed the embedded tracking, which means the client no longer has an open rate, and we judged the program on replies, meetings and revenue instead.
- We repeated the ad storylines in the email subject lines. A reader who had seen a storyline on LinkedIn met the same one in the inbox, which built recall across the two channels.
The impact
Within three months, the positive reply rate reached 7%. The period produced two conversions, which came from the email replies and booked $40,000 in revenue. One was a $10,000 proof of concept and the other was a resource deployment worth $30,000 over six months, and together they returned ten times the $4,000 ad spend.
| Measure | Before | After three months |
|---|---|---|
| Email open rate | 1.7% | Not measured, because tracking was removed |
| Positive reply rate | 0% | 7% |
| Positive replies | None | About 280 |
| Emails sent across the three months | Not reported | 20,000+, or about five for each person |
| Meetings booked from email | 0 | 6 |
| Conversions in booked revenue | 0 | 2 |
| Total booked revenue | None | $40,000 |
| LinkedIn ad spend over six weeks | None | $4,000 |
| Ad spend for each meeting | None | About $667 |
| Estimated cost of mailboxes, domains and data work | None | About $1,000 |
| Total cost, ads and infrastructure | None | About $5,000 |
- About half of the positive replies came from people who had seen the ads. That is roughly 140 people out of about 280, and the other half replied by email alone with no engagement with the ads.
- The ads reached about 1,600 of the 4,000 people on the email list. About 140 of them replied positively, a rate of roughly 9%. Among the other 2,400 or so people the ads did not reach, about 140 also replied positively, a rate of roughly 6%.
- The campaign served about 53,000 impressions to an estimated 4,800 people and drove about 213 clicks. The audience held 12,000 people across about 1,600 accounts, and the ads reached about 40% of it, with each person reached seeing them about eleven times on average. That is a click-through rate of 0.40%, a cost of about $19 per click and a cost of $75 for every thousand impressions.
- About 21 people downloaded the asset. They were the people moved into the separate nurture system, at a cost of about $190 for each download.
- Six meetings produced two conversions. One in three meetings turned into booked revenue. The booked revenue equals ten times the ad spend.
What has to stay true
Because the ads and the infrastructure rebuild changed within the same three months, this write-up cannot say how much of the lift each one produced. Removing the tracking means we have no open rate for the period after the rebuild, which leaves the 1.7% baseline with nothing to be compared against. The program is judged on replies, meetings and revenue instead. The 7% figure counts only positive replies and the 12% counts every reply, and we lead with 7% because it measures people who wanted to talk. The baseline positive reply rate was zero.
The 7% was measured on a warmed list of 4,000 well-matched people, many of whom had seen the ads over six weeks. It describes what a warmed list can return and should not be read as a forecast for a cold one. About half of the positive replies came from people who had seen the ads, which leaves the other half unexplained by the ads alone, and the rebuilt sending setup and the matching storylines may account for part of it. The people the ads reached replied at a higher rate than the people they missed, although the two groups were not randomly chosen and may have differed in ways we cannot see.
Two conversions are a small number, and the result describes one client over one quarter. The $30,000 resource deployment is booked across six months and is not cash received yet. The result also depended on the targeting holding up, since a list full of the wrong buyers would have been warmed with the same ads and produced the same replies with no one ready to buy.
Key takeaways
- Celebrating out-of-office replies and double opens means the team is measuring the system rather than the buyers. Agree early on which number represents a person who wants to talk, and report that one.
- A well-targeted list can still ignore you. Fit tells you who should buy, and recognition decides whether they respond to the message.
- Ads and email work better when they tell the same story. Repeating an ad's storyline in the subject line gave recipients something they already recognized.
- Judge the ad spend by what the list converts. Two conversions worth $40,000 mattered more here than the 213 clicks behind them.