How transactional email campaign proved to be zillion times better than a newsletter? – Bulk and Transactional Case Study.

How transactional email campaign proved to be zillion times better than a newsletter? – Bulk and Transactional Case Study.

A one thousand times higher effectiveness than newsletter? Welcome to the world of the big data. The article presents data showing what can be achieved by using a marketing automation system. React to customers’ behaviours in real time – such as viewed products or abandoned carts – and engage your clients.

How to conduct effective marketing based on the knowledge about customers?

Marketing communication with customers brings measureable benefits for an e-shop, but one has to know how to conduct it. A common way used by online shops is to send a newsletter to customers in their database. It is a method which is proven and easy to implement. Unfortunately, it is not necessarily the most effective one. The problem edrone aims to address is to find as effective ways of engaging customers as possible. To meet the needs of many e-commerce entities, we have decided to give our customers a wide repertoire of ready-made marketing scenarios.

The scenarios we have developed are called engagements. They are ready-made plans of e-mail communication sent to the shop’s customers. What is important, the effectiveness of these techniques has been tested by us. From among many ideas, we have chosen those which work best. We are continuously working on new ones as well. The current trend in marketing is to communicate with customers through personalised messages, and do it in an automated way at the same time. That is why in edrone we introduce techniques which employ machine learning (I encourage you to read the article Product Recommendations Deal with it!).

Serial e-mails and those based on the knowledge about the customer

In edrone, we distinguish between two categories of engagements: marketing and behavioural. The difference between the marketing and the behavioural scenarios results from the source of input data and the time at which we use the said data.

In the case of marketing strategies, it is the marketer who designs the communication which will be sent to a specific target group (e.g. to all customers of our shop or to a defined group such as trendsetters or customers who spend the most). The information which the shop’s customers will receive is the same for everyone, the only difference being certain dynamic parts of an e-mail such as the language version. It is also the marketer who decides about the time of sending an e-mail. A classic newsletter is one of the techniques described. An example is a message of the following type: „Valentine’s Day Discount Voucher”. A more developed newsletter is an A/B newsletter. It makes it possible to test two versions of an e-mail which differ in, e.g. the layout, on a limited number of customers and send the better version to the other ones (I encourage you to read A/B Tests. How to Make it Reasonable?).

Image 1. Example of an engagement in edrone Mission Control: a dynamic newsletter design.

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The second category is the so-called behavioural engagements. Their strength is that they are based on realistic actions of online shop’s users. They do not have a specific date on which they are to be sent. The trigger is a concrete action by the shop’s user. Behavioural engagements are also called transactional, since they are often connected with transactions performed by the shop’s customers.

In the case of behavioural scenarios, an even greater part of communication (compared with marketing e-mails) is dynamic and personalised. An example of a behavioural strategy is the recovering of abandoned carts: Mr Matthew visits our shop and adds a product to the cart. If he does not purchase anything, he will receive an e-mail after 3 hours asking him whether he would like to finalise the purchase or whether he is still interested in a given product. If he makes the purchase, he will get a discount.

Image 2. Restoring baskets an example of engagement which is based on customers’ behaviour.

screencapture-control-edrone-me-recover-carts-1480412497497

Below, we present ready-made scenarios which our customers frequently use, divided into the marketing and behavioural ones (compare with Picture 3). Popular customer engagement scenarios in edrone are as follows:

    • marketing engagements:

–       Dynamic Newsletter – a classic newsletter improved with dynamic elements such as a placeholder with recently viewed products, bestsellers and one-off vouchers;

–       Custom newsletter – it is based on the dynamic newsletter engagement, but makes it possible to reach very specific groups of consumers;

–       A/B Newsletter – dynamic newsletter with the function of testing e-mails before sending them to a larger number of customers;

 

    • behavioural engagements:

–       Get Customers Back – contact with the customer after a specific number of days since they last viewed products in the shop and did not make a purchase;

–       Viewed products – it is an extended version of the get customers back; the marketer can set as many as four different messages which will be sent to his shop’s customer, e.g. after 1/3/7/14 days;

–       Abandoned Carts – recovering an abandoned cart;

–       After Purchase – a message sent after a purchase;

–       Loyalty Programme – a message encouraging to another purchase; after exceeding a set threshold of money spent in the shop, the customer receives a discount voucher;

–       Sgning up for Newsletter – a user leaves their e-mail address in response to a pop-up on the shop’s website or in an embedded field for entering e-mail address on the shop’s website; as a reply, they will receive two e-mails – the first one with a request to confirm e-mail address and a second one thanking them for Newsletter subscription.

–       Recommend – suggesting customers the products they might be interested in. Recommendations are made on the basis of the products bought by other users.

We have recently launched two new behavioral engagements:

–       Wishlist – notification of product availability;

–       Crossselling a scenario similar to after sale, extended with the ability to specify the categories of products for which it is enabled.

Image 3. Marketing strategies available int he Mission Control.

screencapture-control-edrone-me-engagements-1480412527204

Let us arrange edrone functionalities in terms of the value of goods sold, attributable to every e-mail sent (see Chart 1). The most effective method is the “Custom Newsletter“. Its high efficiency results from the possibility of reaching very specific target groups, e.g. customers who responded positively to marketing campaigns in the past. The “After Sale” scenario is not far behind it. The effectiveness of this engagement is not surprising – if the customer has made a purchase and is happy with it, there is a good chance that they will make another one. The “A/B Newsletter” and “Abandoned Cart” are moderately effective. In turn, the lowest in the list is the “Dynamic Newsletter”, which is about 400 times less effective than “Custom Newsletter” or the “After Sale” (sic!). Does this mean that we should not use the “Dynamic Newsletter”? Not necessarily, but if we can decide, it is better to use the “A/B Newsletter” or the “Custom Newsletter” (which allows responding accurately to customers’ needs with a little more work on the part of the marketer).

Chart 1. Value of products sold divided by the number of emails sent.

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To have a full picture, let us also look at the value of products sold per engagement (see. Chart 2). “After Sale”, which in the previous graph occupied second place, has moved up to 1st place. The “Dynamic Newsletter” brings major benefits to online stores. The value of the products sold in this engagement represents nearly 70% of the amount generated by the “After Sale”. Such a large value may seem paradoxical if you remember that the “Dynamic Newsletter” brings the least money per one e-mail sent. In this case, the scale effect – the “Dynamic Newsletter” is often sent to all customers registered in the e-store database. In this case, quantity turns to quality – at least in revenue. High values are also attained by 2 engagements associated with restoring clients (“Abandoned Carts” and “Restore Clients”) and “smart” newsletters (“Custom Newsletter” and “A/B Newsletter”). So far, “Recommend” has brought the least money, but keep in mind that this is a newly-launched engagement.

Chart 2. Total value of products sold by engagement.

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Engagements in detail

Let us take a look at yet one further feature of marketing scenarios available for marketers using edrone. The plots, which will be presented shortly, show conversions at different stages of a path leading the shop’s customer from receiving an e-mail from the edrone system to the purchase. This path is also called the tunnel of sales. In edrone, we monitor carefully the said path. It consists of the following stages: receiving an e-mail -> opening an e-mail -> clicking on a link (visit to the shop) -> adding a product to the cart -> purchase. Conversion is, for instance, the number expressing the ratio of the number of received e-mails to the number of e-mails which have been opened. Thus, it is a value which is always in the range from 0 to 100%.

The following plot (Plot 1) shows a comparison of conversion at the stage: receiving an e-mail -> opening an e-mail, on the so-called box plot. For each engagement, a horizontal box (hence the name of the plot, a “box plot”) shows a range of 75% of the most popular conversion values. The dashed lines are the so-called “whiskers”. They represent the minimum and maximum values which are extremely rare (a few occurrences for many hundreds of cases). A black dot inside box stands for the average value of conversion for a given engagement.

The highest average conversion in the first stage of the purchase path, i.e. the one involving opening e-mails, follows the “Newsletter subscription” scenario. The second stage involves “After Sale”. These are two engagements, where the customer expects to receive e-mails from the store. Looking at the “boxes” on the chart, you may note that the “Loyalty Program” has a broad conversion range. This means that in this scenario, there are both shipments of relatively low and relatively high conversions. The “Dynamic Newsletter” falls behind in this summary. In the case of the “Custom Newsletter”, the number of observations was limited, and therefore it is not shown in the chart. In other words, it is an engagement which is not yet very popular among edrone customers.

Plot 1. Email open rate by engagement.

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Note: Custom newsletter is not shown on the chart due to the not a sufficient number of observations .

However, we are more interested in the overall effectiveness of marketing activities as measured by the end result, i.e. usually the value of the sold goods or the obtained margin, rather than in the number of opened e-mails. Such a chart would not be legible due to the fact that similar values of conversions measured this way for each engagement would be difficult to compare. Instead, let’s examine the next stage of conversion. Chart 1 presents the percentage of the e-mails opened. The logical further stage starts from clicks on links in the e-mail. Chart 2 shows the conversion calculated at the stage of opening the link in the e-mail to make a purchase. This is the rough percentage of entries to the store from an e-mail that ended up making a purchase in the e-store. In this perspective, the highest conversion values are shown by “Newsletter subscription”, “After Sale” and “Abandoned Carts”. “Recommend”, with its good conversion against other engagements, surprises us positively. The “Dynamic Newsletter” falls behind, even though it did strike a few “golden shots” – which means a single observation with high conversion. On the chart, these are circles which represent outliers. This can both testify about a stroke of good luck, or a job well done and substantive knowledge on the part of the person preparing the “Dynamic Newsletter”. The “Loyalty program” has the same low average conversion (indicated by a black dot), but the width of the box indicates that better conversions are far more frequent in that engagement than in the case of the “Dynamic Newsletter”.

Plot 2. Conversion rate from clicking on a link in email to order. For clarity of chart the axis is limited to 4%.

4Note: Custom newsletter is not shown on the chart due to the not a sufficient number of observations

Sniper rifle better than cannon

Time for conclusions. I thought that I did not have to convince you that personalised communication sent to customers is significantly more effective than mass mailing. Even if we send an ordinary dynamic newsletter, we can do it a lot more effectively. The key is to possess the knowledge about customers and skills of using it. Despite that the dynamic newsletter  brings real money for the business, as simple an idea as an A/B test significantly raises its effectiveness. And in this case we additionally use only one piece of information – which version of e-mail is more convincing to our customer. And the “Custom Newsletter” came out best of all engagements in terms of the number of products sold per e-mail! In this respect, it is even slightly better than “After Sale”. The “Custom Newsletter” is so good, because it allows targeting messages based on selected segments. In terms of the total amount of products sold, however, behavioral scenarios are absolute masters of performance. A total of 60% of the value of products sold comes from behavioral scenarios. The “After Sale” alone brings 1.5 times more income in this respect than the best of the newsletters: “Dynamic Newsletter“!

The tools available to marketers are becoming more sophisticated. As a result, the customers are more satisfied, because instead of unsolicited mass e-mail, they receive messages that they may relate to and which are of interest to them. But in order to be able to customize your marketing message, you should use strategies based on customer knowledge. Therefore, you need a system to collect data about the store users, to respond to their actions in real time and, finally, to automate marketing communication. A system such as edrone.

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Maciej Mozolewski

Maciej Mozolewski

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