Category Archives: Conversion

Don’t just aim for an open with your subject line

Ever heard someone say the purpose of the subject line is to get the open? This is short sighted and the purpose and impact of the subject line goes much deeper. The thinking behind a subject line should be more than “what will make someone read this email?”

A case in point is some work I’ve recently completed for Coinks Deals. I’d like to share with you what was learnt about subject lines and how to best communicate with a large dormant database.

Coinks Points introduced a new deals service for their members and wished to provide these deal emails to members who responded to an introduction email about them. Coinks have millions of members, including hundreds of thousands of who had been suppressed from contact for over 12 months. The challenge was how to message to their entire member database, including the dormant members.

The messaging strategy I developed was a four email sequence using a high degree of personalisation to make connection and re-establish trust with members. Several tests were developed to optimise each step of the sequence, testing a variety of elements, including of course subject lines.

As always with testing, the results were insightful and I’m going to focus on one of the subject line tests and what you can learn from it.

For the third email in the sequence to the dormant segment, one of the tests was of these two subject lines:

Subject A: Are we still welcome in our inbox?
Subject B: Was it something we said?

The email itself was a short mostly plain email with a few links and a couple of central buttons shown below

The subject line B gave a 67% higher open rate. However, what was interesting to show the impact of the subject line beyond the open was the ratio of clicks on the above two buttons.

For subject line ‘A’ the ratio of clicks on the first button to second button was 6.5 whereas for subject line ‘B’ it was 2.8. Customers with subject line ‘A’ were more inclined to click the first button. The test cell sample size was 12,000 and the difference in clicks was statistically significant.

The difference in ratio was due to the different subject lines, it changed how customers read the message and what they did as a result. In this case “Are we still welcome in your inbox?” prompted the customer to consider this very question and whether their answer is yes or no. Whereas “Was it something we said?” does not prompt the direct question and the more conciliatory tone creates more interest in deals.

In the many tests I’ve run over many clients I’ve time and time again seen that what happens in the email is skewed and changed by the subject line. The subject line should be designed to get the right people to open not the most people, the right people means those most likely to take the action you want. Plus the subject line should frame their thoughts correctly.

The subject line is used by customers to self-qualify, if the subject line does not accurately qualify the right people then customers who might have taken action do not open and conversely some open only to find it’s not the right message for them. In this case the risk is customers become less inclined to open again since they found they wasted their time previously.

Summarising two key learning’s:

When testing subject lines don’t stop evaluation at the open rate, get more insight by looking deeper at which individual links were clicked and the call to action of each, to learn why the subject line created a particular result.
Create subject lines with the call to action in mind. The power and impact of the subject line goes further than getting the read, it’s about getting the action and not just the read.

This was just one test out of many over a series of four emails. The compounded gain across the whole email sequence was an impressive 190%.

Next time you think about subject lines don’t focus on just getting the open but setting up the right thought sequence for the call action.

Acknowledgements: My thanks to Coinks Deals and Emailvision for permission to publish the results from this work.

How to optimise the timing of an abandoned basket email campaign

1 Reply

Using an abandoned basket email to recapture lost sales and improve website conversion is becoming increasingly popular with website owners keen to optimise conversion in their basket or cart process. For those of you who are unclear on how these emails work, here is a quick explanation.

Your customer visits you website and starts the process of purchasing something from you. However, at some point, before the sale is complete, the customer leaves.. An email is then sent to the customer, encouraging them to return and complete their purchase. These abandonment programmes can range from a single email sent shortly after the basket was abandoned, to multi stage programmes spanning several days. Websites that use them, find they improve conversion, so they are becoming a “quick win” conversion tool.

One of the most common questions from ecommerce businesses, planning this type of campaign is “when is the optimum time to send an abandon basket email?” It’s one of those “how long is a piece of string” questions. It could depend on the type of business you are, and the products or services you are selling. If you are selling small low value consumables, people might make up their mind within hours, but if you are selling larger value items such as investments and holidays, you might need to give your customers a little longer.

To discover the optimal time to send your emails, start by looking at your response data. This will give you an initial guidance as to the length of the conversion window (in time). Look at the customers who abandon their baskets, and track the delay between abandonment and subsequent re-visits and purchase. This type of response curve analysis will give you a good idea of when most people return (is it hours, days, weeks) and it is around this time that your first email should be set up.

I say “start” with response data, as this isn’t all you should rely on to indicate the optimal send time. Abandonment emails are no different from any other type of email marketing, especially in regard to testing. Your data analysis will give you the initial guidance on timing but it will be your testing that will give you the greatest insight for improvement. Once you have established a benchmark for your first email (based on analysis or your customer knowledge) it is important you try sending emails at different time points after abandonment. These can be in addition to your benchmark email, and although earlier emails will inevitably pull some revenue from the benchmark email, it will give you a good idea when the ideal times are likely to be.

So, in short, if I were to choose some “must do’s” for basket abandonment emails, they would be;
• Analyse your data
• Choose your benchmark
• Test to optimise the process

Most importantly, never stop testing!. It is easy to think the process is as optimised as its going to get, but the environment changes around you. Customers change, the economy changes as do the actions of your competitors. The only way to stay on top of all of that is to test, test, test.

No Hang-Ups Here: How to Avoid Landing Page Disconnection

Join us at the International Email Marketing Summit on May 16, 2012

LinkedIn drive revenue with optimised email

1 Reply

In the last quarter LinkedIn earned $33.3 million from Premium membership subscriptions. That’s 20% of LinkedIn revenues and its grown 87% in the last year.

Persuading more of the 90% of free members to upgrade is a major revenue opportunity for LinkedIn.

LinkedIn are using email to convert members, sending a free one month trial offer. I am a LinkedIn member and after many years still on the free package. As an early adopter of LinkedIn this makes me a target for Premium membership upgrade.

Just as I was putting the finishing touches to a new email copy & creative training deck of 87 slides a LinkedIn upgrade offer dropped into my inbox. It demonstrates several of the principles I’d just covered in the slide deck.

LinkedIn have optimised

What happened next was even better. I found a copy of the same offer from last November in one of my email folders (LinkedIn have tried a few times to convert me).

The difference between the email now and from last November is an excellent case study in email optimisation, so let me share the key elements of what changed and why.

Before

After

Another smart move

Not only is LinkedIn (a social network) smart enough to use email to drive revenue but they also send an urgency based reminder email shortly before the offer is due to expire. A second urgency based email to follow-up on an original offer always improves conversion.

Email addresses DO have a “best before” date

2 Replies

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.

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.

Sales impact of ratings request emails

3 Replies

The four key eCommerce marketing trigger emails are; welcome, transaction confirmation, basket abandoned and ratings/review request. Of course there are other opportunities for trigger emails such as Birthday, back in stock emails, win-back and more, however those first four emails are the key emails to put in place before any others.

Here I’m looking at the ratings and review request email. Social proof ratings and reviews have become essential in eCommerce, Reevoo benchmark the average sales uplift due to reviews at 18%. The natural human instinct is to value the opinion of others. My six year old daughter demonstrated this to me. I’d pulled up a page of Nintendo games for her to look at. A few seconds later she exclaimed how one had four stars and another 284 comments. I hadn’t explained social proof or reviews to her and I’m sure its not something taught at school. She seemed to naturally ‘get it’.

A very effective way to build the necessary ratings and reviews is to send a post purchase request email. When Argos implemented such a practice they found 10% of their customers provided a review. If you consider how many purchases you have then 10% is quickly going to add up to a lot of reviews.

The following charts show two ratings examples are from Reevoo:

Which review would you find more persuasive? If you are like most people it will be the one on the right.

The most interesting point about these two bar charts is that they are for the same product. The only difference was reviews for the chart on the right were proactively requested by means of a post purchase email. By asking there is a difference in not only quantity of reviews but the number of positive reviews.

This difference is easily explained. If not asked for feedback, only the less satisfied customers are likely to make the effort to find out how to make a rating and provide it.

Here are some tips for a good review request email.

The reivew request email should be sent a few days after the customer has experienced the product or service. This should be enough time that they have developed their opinion and not so long that the enjoyment of the new purchase has passed.

The email subject line and body should reference the item purchased.

The copy should be short and clear with a well positioned call to action button.

The process to provide review should be quick and easy. A simple star rating could be collected right from within the email using images for each of one to five stars. That’s easy.

Avoid clutter that could distract from the review request.

Remind the customer of your normal support and service channels. If they are not happy, you will want to know directly rather than have a poor review.

ClickZ recently posted this model for ROI calculation of reviews and user generated content and in the last dotMailer ‘Hitting the Mark’ report only 48% of companies studied sent any sort of post purchase email. There is clearly opportunity for many to improve their bottom line.

Oh, and yes I did end up buying the Nintendo games for my daugther that she picked out from the ratings.