Data Hygiene and Compliance

Automated outbound can get a bad rap, but when it's done right it doesn't have to. Let's be honest with each other - the reason why people don't like cold emails is because it feels like spam. Spam is a dirty word and was a symptom of an early internet that didn't know how to stop it. People were not savvy about the stuff they should trust, and bad actors took advantage of that.

How To Not Be Spam

Here is the uncomfortable truth, though: some cold email is spam. When automated campaigns indiscriminately target leads without any consideration of whether they'd benefit from the product or service being offered, there is nothing that separates it from spam. Spam is purely a numbers game. Back before spam filtering was a thing, the cost of sending out an email was basically nothing. If you sent a million emails and even 0.1% of them responded, you could get thousands of potential customers. That was the strategy.

Although the cost of sending emails at that scale has gone up, the strategy of casting a wide net and hoping enough people respond is still in the minds of many marketers when they think of outbound and cold emails. This is not the approach you should be using. Instead, you should be framing your outbound strategy as an active effort to understand everything you can about the person you're sending an email to, crafting an outreach strategy that is uniquely relevant to them, and then building infrastructure around that strategy. The goal should not be to scale for the sake of scale but rather to scale strategies that are proven, through data, to work. 

This idea can be boiled down to one concept: respect. Good outbound respects the person to whom an email is being sent. Instead of seeing them as faceless, brainless statistical probability, you should see them as CEOs and team leaders who want the best for their businesses and who might legitimately benefit from whatever you're offering. This means that you probably shouldn't send something to every email address you can find. This will only burn your TAM. As a general rule, contact no more than 100% of your TAM every quarter.

You have to collect data. If you can understand your leads, you will be better positioned to give them the products and services that they need. The plan should be to meet them wherever they are, when they need the thing you are offering, in a language that they can understand and resonate with. The task is to do enough stalking beforehand so that you know what that looks like. 

High-volume is not a pass for low-quality. Every touchpoint should offer something of value to the recipient. Use automation to deliver insights, solve problems, or offer genuinely helpful resources/ samples. It's better to send fewer, highly relevant messages than to carpet bomb with generic content. Data from your campaigns should be used to constantly refine your approach. If a message is not resonating with your audience, adjust the messaging or stop sending that campaign altogether. 

Come up with some strategy for understanding when automation is the right approach, and when human input is needed. Automation should never replace human behaviours but rather should augment them. Human intervention is sometimes required. If you start to notice weird things happening in an automated system, know how to turn it off immediately and fix it. 

Clean Your Data: Compliance and Reputation

There are more technical parts to data hygiene, too. Always honour unsubscribe requests immediately (but do add unsubscribe links to your email as they will land you in spam). In general, you should stay on top of GDPR, CCPA, and any of the other acronyms regulators come up with. The laws are confusing, but the basic rule is that the consumer has rights over the information you keep about them online. Your best bet is to do whatever someone tells you to do, whether it be removing them from a mailing list or completely deleting their data from your CRM. 

Data cleanliness also means making sure that the emails you are sending to are valid and correct. When too many emails fail to end up where you want them to – known as the "bounce rate" – it signals to email providers and spam filters that you're sending mail to people you do not know. This can impact the reputation of your address, which takes into account bounce rates, as well as instances where your email is manually marked as spam, engagement rates, unsubscribe rates, sending patterns, and the quality of content. If your reputation gets too low, all of your emails will automatically go to spam. We call this "burning" your infrastructure.

While it may seem trivial at a small scale, if you are sending out thousands of emails, failing to account for even one of these things can be a disaster for your company and can cost a great deal of money to fix. This is why you must have a clear process in place to ensure that the data you are using is clean and that your copy is correct. 

There are automated processes that can help you clean your data. Tools like NeverBounce, ZeroBounce, or LeadMagic can ensure that your email addresses are validated. Use tools like Scrubby or Bounceban to validate catch-all email addresses, which are a type of inbox that automatically accepts all mail sent to a domain (regardless of who the intended recipient was). Building these into your workflow can ensure that you don't burn through your emails without getting any of the engagement that you'd want. 

Another important process is the consistent deduplication of data. Although many of the mail systems we use do this automatically, sending multiple of the same message to the same person is, at best, a good way to appear annoying and, at worst, an easy way to break unsubscribe laws. Be careful, though; sometimes duplicates are not actually duplicates (and vice versa). For example, A Shopify URL and a website URL might not be the same – even though they represent the same business. This is why human oversight and a kind of "quality assurance" are hard to replace – even as AI tools get better. 

Finally, data decay is real. Information starts to become obsolete the moment it is collected and stored. B2B data decays at about 70% per year. Make sure you have a plan for this. Create processes to regularly verify and update your data. Yes, this is a pain and is potentially expensive, but you have to do it. Data audits are essential. Go through your database and spot-check some entries to see if they are still up to standard. Do this quarterly as a minimum. 

Check for accuracy, completeness, and compliance. Also, validate your data sources. Some will claim to update every 30 days, but in reality, it's every two years. Why? It's cheaper for them, but most folks don't check. Don't let them pull the wool over your eyes.