If you’ve done outbound sales via email you’ve probably noticed that some of your email cadences stop due to Out Of the Office (OOO) auto-responses.

You are not alone, we noticed the same thing and felt there should be a better way to deal with this. Here’s what we did.

### The Problem

While doing sales for Amplemarket and trying to maximize the efficiency of our process, we noticed that on average 10% of the prospects we contact at any point in time are OOO. These prospects use automated replies that cause the follow emails of our cadences to stop.

Our sales team was not happy with this and wanted to find a solution. While we respect the prospect’s OOO time, it doesn't mean that 10% of potentially interested prospects have to be lost right out of the gate.

We needed to find a better way to handle the problem regarding the stopped email cadences. In order to do so, we analyzed the content of all the OOO responses and looked for patterns. After going through our entire dataset we saw that most emails had a combination of 2 things:

• a return date (E.g.: "I’m on Out of office until Monday")
• an alternative Point of Contact (POC) (E.g.: "I’m on Out of Office, please contact john@amplemarket.com for marketing needs");

### The Insight

The OOO messages were giving us 2 additional pieces of information that we were not using.

With the return date & alternative POC we could design a workflow in which we did not lose these prospects. In fact, we believed we could have a set of automated actions that not only could prevent us from losing contact with the 10% of people that were OOO, but also reach out to new potentially interested prospects that were being mentioned in the OOO email.

### Designing the Sales Workflow

We started by dividing it into 3 parts:
1. Detect an OOO response
2. Handle contacts that have a return date in their OOO message
3. Handle contacts that mention an alternative POC in their OOO message

##### 1. Detect an OOO response

This part was easy because at Amplemarket we had already trained a machine learning algorithm to categorize every email we get from a prospect according to several sales specific situations such as: interested, not the right person, Out of Office etc...

If you want, you can test our email classifier here.

##### 2. Handle contacts that have a return date in their OOO message

After our classification engine identified an email as an OOO we needed to extract the return date. To do this, we trained a feature extraction model that was able to identify and extract any date reference in an email, such as "next Monday","this Quarter", "by the end of the month","Friday 15th" and convert it into a standardized date format MM/DD/YYYY.

With this information we can pause the campaigns when we receive an OOO response and resume contact a few days after the prospect returned to the office.

Here is what we used when resuming contact with a person that was OOO:

Hi {{first_name}},

I know that you just got back to the office and I wanted to give you a few days to go through your inbox.

Did you manage to take a look at my email?

##### 3. Handle contacts that have an alternative POC in their OOO message

We started by looking into the content of the OOO messages with alternative POCs and found 2 types of emails being mentioned:

1. Shared Inboxes (support@, team@) - prospects usually pointed to shared inboxes for urgent situations
2. Other colleagues within the company

While the shared inboxes had little value in the sales context, the second category of emails seemed promising - most prospects were pointing us to the person within the company that was taking their responsibilities while they were away (e.g. a lot VP of Sales were pointing us to a Director of Sales while they were away).

With this in mind, we built a workflow that was able to recognize the emails that were present in the body of the OOO response, eliminate the ones that were shared inboxes, and finally automatically reach out to the alternative POCs that made sense.

#### Email Campaign

When sending out a new email campaign to the alternative POCs we let people know why we are contacting them and that we had gotten their email when reaching out to person X within their company.

Subject: hi {{first_name}} -  contact from {{third_party_first_name}}

Hi {{first_name}}, I was pointed your way when reaching out to {{third_party_first_name}}, who was Out of Office.
...


Here is a comparison of the initial and final workflow for the OOO case

#### The Results

These were the results we received from our OOO campaign compared to our regular campaign

What we saw with this new OOO workflow was a surprise even to us. The OOO campaigns generated 33% more opens and 2x more replies than the regular outbound campaign and these campaigns were going out automatically without any extra effort on our end!

The implementation of these 2 features (pause/start campaigns + reaching out to the new POCs) had a substantial impact in an even more important metric - the number of monthly calls with qualified prospects, which increased a staggering 42%! Additionally, the assumption that the alternative POCs mentioned in the OOO responses could also be valid prospects was true!

#### Final Surprise!

We saw firsthand that any sales rep who is not doing this is leaving lots of deals on the table. We also know that even the most disciplined rep will have trouble keeping up with this manual and tedious daily tasks:

• extract the OOO emails
• manually restart stopped campaigns
• find out potentially good prospects in the alternative POCs
• add these prospects to relevant campaigns etc.

So we are happy to announce that this workflow has been integrated in the Smart Actions section of your Amplemarket dashboard and can now be used by any Amplemarket user :)

Amplemarket Team!

If you have any questions or suggestions feel free to reach out to team@amplemarket.com. You can also follow us on Twitter.

Thanks to Paul Maass, Andrew Wolfe, Joe Zaghloul, Bryan Elsesser, Robin Allenson, Brian Sorhaindo, Gustaf Rössner, Sam Yousefian, Lindsey Colferai and Nate Nordstrom for their feedback on earlier drafts of this article.

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