Category Archives: Frequency

Goodbye “channels” – Welcome the marketing “channel of one”

The practice of creating a seamless customer experience across digital channels has been a common marketing challenge for a long while now, and integration of some offline and online channels through campaign segmentation is the norm. However, for most of us it is difficult to get a grip on every part of the customer experience.

To put this into perspective, there are typically more channels or touch points throughout a customer experience that are entirely generic and not personalised at all, versus those that are. They are not personalised by name, proposition or offer, call to action, location. None of that. This is diluting the effectiveness of a CRM strategy because we don’t have a clear understanding of what every individual experiences through every single channel. But this is changing.

Take a look at this:

Technology is beginning to bridge some of the knowledge gaps to identify non-converting prospects who visit their retail stores. Some brands have tried to patch over this marketing need with solutions such as in-store wifi, but this newer technology is incredibly powerful to marketers. The customer experience in the video above could have resulted in a simple browse and no sale. The marketing opportunities created from understanding that experience through the data collected, will help us to follow-up appropriately with the right content, at the right frequency at the right time – all with an enriched profile of that customer.

The marketing challenge is beginning to shift towards a desire to converse “sequentially” with prospects and customers through any channel at any time. Sequential messaging across multiple devices, locations and mediums. All of these could be personalised, tailored and in a defined, tested and optimised sequence:

  • In-store offers and personalised greetings
  • In-product messaging (some cars are already enabled in this way)
  • In-app messaging
  • Email
  • SMS
  • Website
  • Outdoor advertising
  • Direct mail
  • Delivery messaging

What would this list look like for your brand?

Algorithms could be developed, to enable CRM platforms to intelligently learn and adapt to the best performing sequence of proposition, content and timing. Automatically.

What does all of this mean for Marketers?

Marketers will soon be spending much less time thinking about which message to send through which channel, but more time deciding on the right sequence of messages with the channel serving as a distribution channel. I like to think of this as ‘the channel of one’.

 

Are high open rates holding you back?

Our findings last month on the Obama campaign caused a lot of debate but the bare facts of our analysis still stand – had Obama’s team optimized for improved open rates, their send volumes would have dropped and their all-important donations would have followed.

Open rates remain a widely used and hugely misleading measure of performance and engagement in the email industry. At best they give you an idea of a campaign’s performance in isolation but at worst they lead email marketers to focus on optimizing the wrong strategies for their email program.

Here we discuss how to identify if maximizing open rates is holding you back and how to go about identifying the strategies that will have the biggest impact on your results.

The open rate paradox

Using EDS Analyst we examined the relationship between open rates and total unique opens for the top 200 email senders by list size in the US for 2012.

We were confident that, like the Obama campaign, there would be an inverse relationship between rates and totals – so as rates increase, totals decrease and vice versa. We call this the open rate paradox or to paraphrase a popular sports trusim: rates are for show, totals are for dough.

Each dot on the graph below represents a single sender and we picked out some well-known brands as reference points.

Sure enough, the graph shows that for most large senders, there is an inverse relationship between open rates and the total number of opens – the higher the open rate, the lower the number of total opens. Rates are for show.

It’s also no coincidence that nearly all of the brands with the biggest lists (orange dots) also have highest number of total opens because they are sending more opportunities to open.

Although opens don’t directly correlate to revenue, even the most avid fans of open rate maximization would agree that the more people that actually open your emails, the more engaged your database and the more revenue or conversions you are likely to generate. Totals are for dough.

Keep it simple – focus on just three strategies

If your goal is only to improve open rates, then your strategy is simple: halve your list by suppressing your less active subscribers and watch those rates soar… and those total opens plummet! But if your goal is to increase total opens, then the bell curve in the graph above helps define three clear strategies:

  1. List size:
    Has the biggest impact on totals and can be improved independently of the other two.
  2. Increase send volume:
    Significantly increases total opens for relatively little effort (low effort to gain ratio).
  3. Optimize for rates
    Increases total opens but requires the biggest effort (high effort to gain ratio).

Most brands are clustered towards the lower middle of the curve because it’s the easy place to be. By and large, they all put a similar amount of effort into their program and use the same undefined strategies.

The outliers, however, go above and beyond in one of three ways – those to the right have very high open rates, those to the left have high send volumes and those at the top are combining high send frequency with very big lists to produce massive send volumes.

In effect, this is the three different strategies implemented to their extremes.

Of course, there are limits to the effectiveness of each strategy and these are defined in the graph above by the orange line to the left (frequency cap) and green line to the right (optimization cap).

These boundaries exist because for any given list size there is point at which diminishing returns kick in for both frequency and open rate. And, as the big empty space to the right of the green optimization cap shows, it’s very hard to send a large volume of email while still achieving a high open rate.

So the basis of a successful email program is to continually grow your list while finding a balance between increasing send volume and maximizing open rates with better offers, targeting, subject lines, etc.

And you find that balance by ignoring your open rates…

Define your strategy by ignoring open rates

To illustrate the effect these strategies have on an email program, we have created a simple optimization chart, below. The green curves represent the impact of send volume on total opens and the brown lines represent the impact of open rate on total opens.

Each intersection represents a hypothetical 10-hour unit of resource, as a means of comparing the effort required to implement each strategy. As you get closer to each cap, the effort required to improve your totals with your chosen strategy increases exponentially.

Imagine your brand is the star in the middle of the curve and you want to take on your leading competitor, the lightning bolt.

If you use open rates to define your strategy, then you focus your resource on maximizing those, route A. Your open rate may now be much better than your competitor’s but they are out-mailing you, so they are still creating twice as many opportunities to buy or convert.

If you choose to increase your send volume, ‘route B’, then your open rate drops but your total opens more than double. However, as you approach the frequency cap, the impact of your strategy diminishes and you still trail your competitor.

If you use totals to define your strategy, then you take ‘route C’, which balances resource between increasing send volume and maximizing open rates. Your open rate drops but you are finally creating more opportunities to buy than your competitor.

Smart email marketing is not just a case of increasing send volume indiscriminately or of only focusing on ever tighter targeting. There is a balance that exists for each brand, you just have to find your own sweet spot.

Total opens the key to optimizing your program?

In this instance, we have highlighted the open rate paradox using total opens because that was the data available. However, we’re confident you will find the same inverse relationship in your own campaigns with total clicks and, more importantly, revenue. And in the end that’s the only metric that matters!

 

LinkedIn: No greater email marketing #fail than over-writing your customers preferences

LinkedInWTF2
I just got this  email from LinkedIn  Subject Line “A change to your DMA: Direct Marketing Association (UK) Limited digests” – the 3rd such email I have had this week about a group I belong to.
In it they tell me that they are going to ignore my mailing preferences and unsubscribe me from the group digests of which I get 1 a week a frequency selected by ME! I have now been forced to go and re-subscribe to the weekly digests of groups that I want to hear from 3 times this week. Do LinkedIn really think that is a good use of my time?

Just in case anyone was wondering, while I am not really a FB kind of person I definitely am an UBER LinkedIn user.

- I am a paid subscriber and highly active – I post, place jobs, recommend stay in touch connect etc.
- I have several thousand connections
- I check my page multiple times a day and use it as my primary vehicle for maintaining my business network. I have my preferences set exactly the way I want them for some groups – no email, others weekly and some daily
- I get 10 or more emails a day from linked in and open about 1 in 3 on my desktop and 80% of them on my mobile
- I click on at least one a day and some days 3 or more
- I save all my emails I currently have 2900 in my Linked in folder of which less than half 1427 are “unread”
- I regularly search for old messages or invites and click on them

So how on earth can a bunch of engineers and/or too clever by half marketers come to the conclusion that they know what I want better than me?
The irony is by stopping the DMA group weekly digest, they are going to reduce the chances of me ever visiting again! I wonder how the DMA and other group managers feel about that.

I can’t understand why having gone to the trouble of asking me to set my preferences LinkedIn should choose to expressly ignore the stated preference from a highly engaged – dare I say knowledgeable – paying subscriber. Surely that is as bad as spamming after all what is so different about these 2 scenarios?

1) I use LI preference centre choose to receive 1 email a week – after 3 months LI decide to unsubscribe me for not visiting the group.
2) I use LI preference centre and choose to receive 1 email a week – after 3 months LI decide to send me daily digests or 3rd party emails from partners they think I should hear from

LinkedIn are insulting their members’ intelligence one would think that someone like me would know how to both unsubscribe or hit the spam button. So if I haven’t done either of those things, it’s probably because…I DON’T WANT TO!

The truth behind the buzz: what really made the difference in Obama’s re-election

One of the big stories in digital marketing in recent months has been about a campaign whose results have a major impact on people around the world – the US Presidential Election. Marketing pundits representing all channels have had an opinion on how Obama’s campaign led to his re-election but I would argue none was more significant than the use of email.

Let me start by saying there is no doubt this election was won by email. Here is a direct quote from an article published by Business Week; “Most of the $690 million Obama raised online came from fundraising e-mails”. And by the way,  $690 million represents nearly 75% of the $934 million raised in what ended up being the most expensive Presidential election in US history. This makes email, by far and away the No1 non-political contributor to the drubbing of Mitt Romney.

So why has there been so little said about this incredible achievement by email marketing pundits, ESP’s or their PR machines? When you look at the fuss made over the 2008 campaign – allegedly won by social media – the silence from the email industry has been deafening. When anyone does mention it, there has been a tendency to attribute the success of Obama’s email fundraising activities to anything other than email.

Some may suggest that without the “age old lessons [and presumably wisdom]” passed down from wise-old DM to rather awkward, gauche and somewhat unattractive email marketing the story would have been very different.

Nothing could be further from the truth. Here is what really happened. Obama won because he sent more email to more people more often than Romney period!

According to numbers put out by eDataSource and Return Path, Obama mailed a staggering 40+M subscribers compared with Romney’s 4M, on some days they sent 350M compared with 26M from Romney. So while relevance, engagement, creative – ugly or otherwise, Subject Line testing etc. did play some part in his success, they pale into insignificance compared to the impact reach and frequency had in his success.

What seasoned email marketers might find surprising (I see this as further proof of the fact that frequency drives engagement) is that the Obama database was more engaged and less likely to view the emails they received as spam. The figures below which I extrapolated from numbers published by eDataSource and Return Path illustrate this clearly:

Obama Read 15.85% Total 6,340,000
Romney Read 7.94% Total 317,600
Obama Delete Unread 9.01% Total 3,604,000
Romney Delete Unread 5.11% Total 204,400
Obama ISP Spam 17.95% Total 7,180,000
Romney ISP Spam 52.51% Total 2,100,400
Obama User-Marked Spam 0.02% Total 800,000
Romney User-Marked Spam 0.03% Total 120,000

 

The Obama campaign raised an average of $17.25 per subscriber, if you assume Romney was able to do the same, he would have generated $69M from email compared to Obama’s $690M. So if you were Romney what would you have learned from this, A) Segment and test your way to $172.50 per subscriber or B) Send email to a lot more people more often?

Email delivers something DM cannot. Broadcast reach at near zero marginal cost.

If you don’t want to leverage that, stop sending email!

I have read lots of peoples’ take on the article and what they found most interesting and would like to share mine – something Bloomberg Business Week chose to call a counterintuitive. I don’t and I think it is an awesome admission: “Most people have a nearly limitless capacity for e-mail and won’t unsubscribe no matter how many they’re sent”. Now read the comments made by the very people who made the campaign successful. Note how few said they enjoyed the blitz yet on average they donated $17.25 each.

Now that’s an insight!

I know for certain that they are not the first people to have worked this out, but they are the first significant entity to come out and say it.

Let’s give credit where credit is due in the 2012 presidential election; segmentation, targeting and testing techniques were the tail, reach and frequency were the DOG!

Setting your email frequency and cadence

I’ve been hearing the phrase email cadence a lot lately and its sometimes been confused with frequency. So let’s look at how frequency and cadence differ and how to set them.

Ring-ring

If you’ve not heard a traditional UK phone ring it sounds like this

That’s a rhythmic pattern of 0.4s ring, 0.2s silence, 0.4s ring, 2s silence, which then repeats.

The cadence is the rhythmic repeating pattern and the frequency is how often it repeats. In this case the frequency is once every 3 seconds.

What does this mean in terms of email marketing?

Often there are several independent streams of email activity running concurrently and these different streams beat together to form the cadence.

Take a scenario of an offers email being sent every Monday, Wednesday and Friday, a newsletter email on the second Thursday in the month and a tips email every Tuesday, then the individual frequencies are monthly for the newsletter and weekly for the tips. The timeline for all activity is shown below (offers in blue, tips in red and newsletter green bars).

The same pattern of emails or cadence is repeated every four weeks, so the overall frequency is every four weeks.

If you have automated sequences of triggered emails for welcome, post purchase, abandoned basket and so on then these are overlaid too.

Setting a contact policy

When setting your contact policy for cadence and frequency think about:

  • Setting a minimum time between emails.
  • Setting a maximum time between emails.
  • Prioritisation or suppressing scheduled sends during triggered sequences.
  • Set many emails on average per month are received per customer.

Having a contact policy like this also means that you can set a clear expectation at time of signup, which will reduce spam complaints and improve deliverability. Daily emails need not be an issue, if that is the expectation.

Make it a user preference?

Should you offer individualised contact policies as a user preference? I don’t believe it always makes sense and this will be the topic of my next post.

Acknowledgements: My thanks to @jvanrijn as it was my recent conversation with Jordie that persuaded me there was value in writing this article.

Email addresses DO have a “best before” date

One of the contentions that surround email marketing at the moment is the issue of when you retire an email address. Leading up to Christmas, when the heat is on, ambitious sales targets tempt even cautious marketers to push out the boat and send to everyone. If an email list is causing deliverability issues, it is quite common for a bit of a clean up to be suggested. It’s not a “stab in the dark” strategy, because when used correctly it can lead to a net increase in response and revenue.

However, you cannot ignore, when retired email addresses are mailed, they often produce some revenue. This almost flies in the face of the no response/retirement strategy, but in reality, some fine tuning is in order to squeeze all the value from your list.

To deal with this issue properly, you will certainly need response (sales) data for your customers, and need to know which email addresses the data relates too. In most instances the full picture of your list can only be achieved through wider knowledge of the customer.

All too often, the most responsive customers are the ones who have been opening and clicking your emails recently. But it’s also important to segment those who are no longer interested, from those that have disengaged from your emails due to a higher contact frequency than their needs require.

The first stage of the solution should be test the differing frequency of those people who haven’t opened or clicked for a while. Although a 6 month open/click window might be fine for some businesses, it might not suit those businesses with a longer sales cycle or a wider range of buying frequency. In these instances, sending mailings for twelve months or even longer might be better, but proper testing should help you decide when a customer is signalling defection.

Engagement/frequency graph

If you have transactional data, you can use the principles of RFM (Recency, Frequency and Monetary value) to build up a model which predicts your most responsive customers. In an ideal world you could marry up the purchase RFM data alongside the online engagement data, to see the point where Recency for online engagement (opens/clicks/visits) signals a lapsed customer.

Using email response data, we create two segments, those that are recently engaged, and those that are not (don’t throw any away yet!). The engaged segment can carry on receiving the main campaign emails at the normal frequency. The less engaged segment now gets a rest (for about three to four times the normal frequency of you campaign emails). So if you generally send weekly, rest this segment for a month.

What we are trying to do is identify a segment within the email database that has stopped responding to emails due to a mailing frequency that is too high for them. By responding to the users behaviour, you are able to make changes to the email frequency of this group.

If people from this lower frequency segment, respond, it is important that they don’t go straight back into the main campaign mailing frequency, but give them more of a rest between mailings.

What we are trying to do is to start down the road of mailing people at a frequency that suits them, keeping them engaged and encouraging them to buy more. Managing frequency is the easiest way to respond to behaviour (or lack of it) but if you have more resource, you could try content too. One of the other top reasons why people stop opening emails, is that the emails are no longer relevant to them. The difficultly with content relevance, is that it relies on a deeper customer knowledge, or web behaviour data.

Unfortunately there will be those email addresses in the list that despite your best efforts will never be responsive again. So, at some point you will have to bite the bullet and let these addressees go. It is important to accept that the damage that is done to the whole email programme (in the shape of poor inbox deliverability and reduction in response) will outweigh any extra revenue gained by mailing these inactive email addresses.

Reactivation – 9 Tips to re-engage with your email list

No matter how successful an email program, how engaging, relevant and timely you think your communications are, over time all email programs will have consumers who no longer want to interact with your brand. Some research suggests that up to 60% of the average consumer list will become inactive after 6 months. What you do about this is a matter of quite hot debate within the email community.

Do you stop sending to the truly disengaged? From one perspective having inactive on your list distorts engagement figures and can have negative impact on the impression of success within an organisation and potential deliverability problems but on the other hand there is a branding effect that is seen when even supposedly disengaged customers have greater engagement with the brand because they see the email in their inbox

The reasons that consumers churn according to Marketing Sherpa range from lack of relevance & too much email at the top through to change of circumstances. The varying reasons will require slightly different tactics to deal with. So here are some top tips in creating a successful reactivation program

1. The first issue to deal with is who to actually reactivate. There is no black and white definition of lapsed customers, however by undertaking some basic recency-frequency (RF) analysis you should be able to see a pretty clear drop off in opens and clicks and put a stake in the ground around what is lapsed for your particular population.

2. As a more advanced tactic I would recommend adding, where possible the monetary element. Logic would dictate that if someone used to not only be engaged with your communication program but was also one of your highest spenders then it worth more effort to get them to re-engage.

3. Also remember that you should always split out those that have never engaged vs those that are truly lapsed since the methods of reactivation and indeed the value to your organisation will be very different

4. Stop sending regular mailing to the reactivation segment. In this way it will be clear that if these people do start to respond it is due to re-engagement activity

5. Unfortunately there is also no hard and fast rules for getting a particular population to re-engage to it will require you to test various techniques to see what works for you. Promotion / giveaways, increased value exchange, garnering feedback are all valid and useful techniques.

6. Testing a variety of offers as well as approaches is also recommended. 2 for 1 offer / or X % discount / additional gift with purchase) have all been successful for a published client because within the target reactivation groups there was quite a wide variety of different profiles

7. The reactivation process should be built around highly interactive experiences – Sun Microsystems for example drove their inactives to a highly interactive and personalised preference centre (see my previous DMA blog article on tips for developing a preference centre) other clients to exclusive online content. It is a chance to renew the value exchange promise with the customer.

8. In thinking about goals and measurement. Firstly ensure that you have a control cell so that you can accurately measure any incremental lift from the campaign. From an expectation perspective it is should be considered incremental rather than step change. In our experience 5% reactivation should be seen as a good result

9. Email lists need a holiday – temporary suspension or resting – can sometimes offer excellent results as shown across a number of clients. One client for example suppressed a group of non clickers for 4 weeks and then when that group received an anniversary sale email they outperformed the control cell by over 5%

Email addresses are a very valuable asset that you spent lots of money collecting, permissioning and building engagement. Not withstanding the long held belief that it costs 5-10x to acquire new customers as to retain existing customers can you afford not to focus on reactivation?