Send Less, do more

How watching Jerry Maguire can make you a better marketer

Jerry Maguire is one of my favourite films. It’s life affirming and does not have any Scientology in it. Those are not exclusive criteria by which I judge a film, but using the films ideals – be more personal in business and not only learn from failure but love it and own it – we can do so much better as marketers and business professionals to try and work by this mantra.

In Jerry Maguire’s mission statement he professes that his industry is full of ‘Slicksters and Hucksters’ who only care about the bottom line and not about the clients. The clients should come first, “I had some bad shrimp and grew a conscience!” he says when doubting his new found clarity. If we are not to doubt who we are as marketing professionals, and survive the tide of ‘Slicksters’ and glorification of what we do, there are few things, asides from our conscience we can rely on. Yes our moral turpitude and personal zeal, but we can also rely on lists and data. I can’t say it enough but your marketing lists and your data and insights that you garner from them, have to be central to your marketing strategy. Especially your email lists.

Having said that and if you are a genuine email marketing cowboy, buying consumer data, flouting EC and UK email law, there is a potential to have the biggest revenue dividends in terms of ROI on email marketing spend. BUT! and I shout this from my lofty keyboard: Tread carefully, very carefully when tip-toeing around this line. Here be monsters, monsters with a 5 year prison sentence and hefty fines if you are caught contravening any anti-spam laws.

And getting down from my pulpit, there is a way you can use data personalisation and data tagging, to help you to keep your lists lean and your conscience warm and fuzzy.

A little history

Having spent 10 years in digital marketing, development and sending out more than 15 million emails, I have had one or two revelatory moments.


Not like that but more like this:


The campaigns and projects that have had a more personal targeted approach have always been the most rewarding and where the most has been learned. During these types of projects revenue has always been a key point but not the point.

Since 2006 the internet has become a place where financial rewards come from relevancy, precision and low-over head business models. With that process, more-over, came the proliferation of marketing collateral. It has always been thought in order to get the most revenue, you need to get your product out to the most amount of people. From 2009 to 2012 there has been an average, 200 to 300 B2C emails a week sent to individuals that are either irrelevant or come to often (— e-Dialog: “Manifesto for E-mail Marketers: Consumer Demand Relevance” 2012), and as an industry we know the stats like this, have heard them, yet ignored them. In a 2015 study by Google Consumer Insights, out of 1830 consumers, 43.9% said they wanted to receive emails less frequently. As a consumer, I only want to receive an email when there is something new or when there is something relevant…to me. And once you have an established brand, it should no longer be true that you have to email as many people as possible. During my time as marketing operations/developer it has become increasingly obvious, that I had to find a better way to ensure ROI and either be ok with there being no end to the amount of emails being sent or change the way we send emails.

From an agency perspective if you take on the work you are duty bound to fulfil the obligation, but how you do it has to be to the best of your abilities. Part of your ability should include certain fail-safes to ensure that you, as an agency/expert are looking after the interests of the consumer.


What I wanted to prove at this stage is:

We need not bother people to the extent we do.

The Theory

From the beginning of 2013 to September 2014 I was responsible for sending roughly 562,000 emails over 6 campaigns. These included app notifications, website and product updates, product or service email blasts and newsletter campaigns. Of those there I would consider a third would actually be of use to an individual and when looking at some of this data over a third would be on a list, had been emailed and done nothing.

Some subscribers would remain on a list for years. Not interacting, not buying, not engaging. The question is why are these types of subscribers on this list? This fostered my idea of “morality in email” — how moral is it to continue sending emails to people that aren’t engaging with them? Posing this question to marketers, they did not really have an answer. The only answer they could come up with is, “Well…they might come back if we send them an incentive…”


I did not get that either. My advice and this will sound a bit crazy….get rid of them. Not at all revolutionary, but what is the point making sure that all subscribers are on a list instead of focusing one the ones that matter.

So from a stakeholder perspective this is hard pill to swallow and I will come back to that in a moment, in terms of getting client/stakeholder buy in. And to prove that it was not worth while for companies to keep hold of this data we began to track the users habits over time and to analyse their click habits from one campaign to another. We wanted to use data sets and personalisation techniques to try and test the theory. We also looked at open rates, and click rates from one year to the next providing a Year on year analysis.

From a SQL perspective, if that’s how you manage your data, you can place timestamps on an individual record, from the first opt-in click,  or from first interaction (including email send), then at certain checkpoints we would take snapshots and report back on redundant subscribers who were not doing anything. The timestamp of a non-responder became the personalised flag with which to set send criteria or not.

If you are managing your data through a supplier, MailChimp for example you can us the api here: to define GET responses for timestamps and provide actionable queries based on when a record has triggered an event. Something to this effect:

"emails": [
      "campaign_id": "42694e9e57",
      "list_id": "57afe96172",
      "email_id": "62eeb292278cc15f5817cb78f7790b08",
      "email_address": "",
      "activity": [
          "action": "open",
          "timestamp": "2015-09-15 19:15:47",
          "ip": ""

And the same for Hubspot here:

Once you have parsed your timestamp to a column to record when the consumer last interacted, you can think about the types of actions or flags you want to create. For us we cross referenced this when the campaign started, and tranched the data into thousands and took data at monthly intervals.

For a monthly newsletter, where we sent out to roughly 10k subscribers we got something that looked something like this:

[visualizer id=”162″]

Non-responders increased and made up almost 30% of the 10k subscribers.


As the year went on more and more people were doing nothing. And this has nothing to do with unsubscribes or creative or execution as we approached the campaign in a fairly generic manner. Open rate was at 18% and click through was at 6%. Which by industry standards was not too bad. And presenting this back to the client they could not understand why this was happening and wanted to know the answers. Is it the creative? Are the call to actions not eye grabbing enough? Creative pitfalls might have been what was wrong, but one smarter client asked the right question, ‘Have we got the wrong type of data?’ The data was made up of newsletter subscribers and purchasers, so users must have done something first, but if we refer to our point of saturation, where if you are not relevant or precise, you are not rewarded.

We therefore had to convince them and prove that this was not some kind of fluke. So we ran the same campaign the next year with slightly different offers, promotions and news, bearing in mind their customer base had not grown to a massive number. And in order to represent the experiment effectively we had to convince them that we had to send the email to the same data set, except for this time taking out the non-responders. And this was the result:

[visualizer id=”166″]

We then compared these results to marketing our own company and other clients with a similar list count. What we found in the most part is that with smaller more targeted lists ROI was either maintained or in fact increased. Smaller data sets = smaller gaps between open rates, click rates and eventual ROI.

Whilst this is not revolutionary its a factor and a pervasive element that more often than not companies, big and small, did not have an effective list management in place. Obviously this keeps me off the streets, but its a fundamental ideology which underpins how I feel we should handle data, to change the way we market to consumers. Why are we contacting these people? Are we still imagining online marketing as an extension of a shop advertising? Are we still following the Wannemaker complaint of: “Half the money I spend on advertising is wasted. The trouble is, I do not know which half.” Wannemaker said this in 1898, are we still in this place? Why are we not looking at the data first?

So what do we do with this revelation?

Do we keep cutting down our lists until we have nothing left? No, ideally what you want is to get the stage where you are sending enough of a targeted email that your subscribers become purchasers and your purchasers are engagers and engagers are listeners, who will identify with your brand and products. It’s also an establishment of your organic list with the knowledge you have not just blasted anyone with a pulse and email address.

The trick here is getting buy in from stakeholders, to try to make your emails as personal and human as possible.


Getting this buy in relies on an acute focus on the performance of email rather than the size of the list.

And in my experience as long as there is a demonstration of effective list data and revenue will not be affected most people are receptive to trying something new. Some clients, however, simply will not care and will not see the value of emailing less people. The value for me is obvious. Yes you are sending less emails to less people. But by that token we as marketers can feel that much more responsible for the lists we manage and the customers we bother. I will always imagine myself as the consumer and wonder if I would want to receive the emails that I am creating.

And if it is understood that these lists are more targeted and more personalised, you can analyse your click through’s from a clean bias. Knowing that your data is qualitative rather than quantitative can provide a much more valuable insight.


So you have your buy in and your targeted lists how do we leverage this to make personalisation art of the equation. I am not talking about a Minority Report kind of way, but using user data to humanise your brand messages and get even closer to that moral line.

Once you have the big moral 3, effective data, buy in and personalisation, you are in a golden ticket seat to use the: THE EMAIL MORALISER 2200 or the ’12 step programme to woo your client to be a better organisation and increase customer satisfaction.’

Now don’t we all feel better about emailing our fellow humans. Join the conversation, or tweet me @AndrewBalerdi. And I leave you with this ultimate line from the end of Mr Maguire’s (Cameron Crowe’s) mission statement:

Let us start a revolution. Let us start a revolution that is not just about basketball shoes, or official licensed merchandise. I am prepared to die for something. I am prepared to live for our cause. The cause is caring about each other. The secret to this job is personal relationships.

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All rights reserved. Andrew Balerdi Copyright 2018.