Email Marketing Tactics from Billion-Dollar Companies

This video clip and those following are taken from CLVboost Founder Dan Faggella’s startup marketing presentation for #BostonGrowthHackers at the Microsoft New England Research & Development Center.  The strategies are break-down techniques that Dan models from billion-dollar companies, like L.L. Bean and HubSpot, that can be applied to your own business models.

Email List Sub-Segmentation to Encourage Engagement, Purchases, Appointments

The “Red Button” analogy.  I’ve spoken about this topic on guest podcasts before, and for good reason.  This phenomenon happens every month with new startups who are still experiencing those moments of fear and uncertainty.  As they survey and line up their gathered prospects and customers, getting ready to send out a weekly or monthly newsletter, they react and slam the red button that pushes out an email to everyone, all at once. This approach doesn’t make someone a “bad” person, but it certainly doesn’t have a whole lot of thought behind its impetus -no real explicit ROI-yielding strategy and no segmentation, more of a “we’re still alive” effort. Screen Shot 2015-07-28 at 12.06.18 PM I’ve used different sized and colored boxes to represent various customer segments.  Step away from the red button and avoid the broad sweep.  Target your emails based on customer segment.  A quick review on two main ways to parse through customer leads:
  • Selection Parsing (What they pick)
  • Contextual Parsing (Where they enter)
Selection parsing is handed to you – you know what the customer wants because they tell you based on their actions and choices.  Contextual parsing is implied – you know what the customer wants because they’ve found their way to a particular site or page. If you look at your core customer list, you should be able to determine three to five categories based on these parsing methods alone. Then the big question becomes, does everyone in your database deserve to be marketed to in the exact same way? The answer is, in 98.97% of cases, a resounding no.  Take L.L. Bean as an example of a billion-dollar company with serious marketing initiatives.  Those pretty catalogs in the mail aren’t a reflexive afterthought.  No doubt that L.L. Bean schedules rotations for catalogs, inserts, combinations of catalogs with emails, etc., all sent to customer groups dependent on gathered demographics, buying behavior, and other marketing criterion. Are your subsets parsed out based on buying behaviors and methodologies?  Some of your customers – the ones with a regular routine of getting out the credit card – undoubtedly deserve more communication, perhaps even a different tone of voice, than others.  How might you might modulate the email list segmentation process the way L.L. Bean does?  What might you test first? [video_player type=”youtube” youtube_force_hd=”hd720″ width=”640″ height=”360″ align=”center” margin_top=”10″ margin_bottom=”20″ border_size=”4″ border_color=”#DDDDDD”]aHR0cHM6Ly93d3cueW91dHViZS5jb20vd2F0Y2g/dj1vQUJiWWUyeXUxWQ==[/video_player]

Collecting Extra Data for More Targeted Marketing Messages

Get more data, sell more stuff.  I call it the “Second Helpings” approach. The best time to get more data is right after you’ve gotten a first batch of data. Screen Shot 2015-07-28 at 12.44.46 PM After you’re given purchase information and a customer email address, think about what else you want to know about a particular customer subset.  A good way to get this extra bit of information is to give the customer ‘just a little more’. For example, take a sports company that specializes in working with players on mental confidence by selling information products.  That company might want to know what it is that makes a player nervous.  Is it trying new techniques?  Playing outside of a hometown? If you can offer an additional product or service (thank you pages are also a model option) with a clear bonus, then you’re in a good place to increase conversion and get that hearty second helping of customer data.  Check out HubSpot as a good example of a company that does this routinely. [video_player type=”youtube” youtube_force_hd=”hd720″ width=”640″ height=”360″ align=”center” margin_top=”10″ margin_bottom=”20″ border_size=”4″ border_color=”#DDDDDD”]aHR0cHM6Ly93d3cueW91dHViZS5jb20vd2F0Y2g/dj1BZjlUM0tTcF90dw==[/video_player]

Segmenting “Newsletter” Emails for Higher ROI

Open rates can go way up when you send newsletter emails to segmented customer lists. Screen Shot 2015-07-28 at 12.53.16 PM Simple segmentation can double your results.  We call this the “Fork and Multiply” strategy.  Envision a company selling skills-based services that has a client base primarily composed of media agencies, content creators, and entrepreneurs.  If that company sends ‘best crowdfunding practices’ as a mass email subject line, they might get an 8% open rate on a 3,000 open list, resulting in 240 opens and 12 buyers at a 20% conversion rate.  This is a decent scenario. But if that company takes four extra minutes to parse lists on the front-end by looking at easily-collected data (surveys, front end, etc. – still anxious about this step?  Inc. published a good, quick read on how to collect data and keep customers), and then makes targeted broadcasts, the total amount of buyers doubles (assuming the same open and buy rates). Using the same email content (give or take a few minor alterations), entrepreneurs get a specific subject line and call-to-action that appeals to entrepreneurs, and the same goes for the media agencies, and the content creators – same email, but targeted approach. A company that gets a ‘little bump’ in each sub-segment can witness drastically higher open rates.  Maybe this still seems relatively small based on one campaign, but using the same list and same routine each month, a company is almost guaranteed more revenue by end of year, which is the better bottom line. I hope the ideas in this presentation were helpful and that you’re able to take the strategies discussed and apply them right away with great results!
– Daniel Faggella
CLVboost Founder
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