X

See the full results by downloading the free case study.

Breaking down DSP Blackrock’s Email campaign (a mini course in email personalization)

Estimated Reading Time : 2 Mins | Knocks : 6107
Customer Profile

DSP Blackrock is a joint venture between two globally renowned asset management companies (AMCs): DSP and Blackrock. With a history of over 145 years, DSP Group is one of the founding members of the Bombay Stock Exchange. BlackRock is one of the largest asset management companies in the world serving a broad range of clients globally.

The Objective

Personalization is the new black.

If you are following the blogs and Twitter handle of fellow marketers then you would start thinking that every marketer in this world is doing personalization to the highest degree.

And then you would go to your inbox and find Pinterest doing this

At least Pinterest made an attempt. Most marketers don’t even move beyond [firstname.fallback=friend’], a comical irony given that we have such a concerted agreement amongst marketers with regards to personalization. The fact is that barely 23 percent of online retailers are able to deliver personalization to some degree.

Personalization is a difficult horse to tame. Very few brands are doing impressive things which brings us to the ‘yearly round-up’ email campaign built by marketers at DSP Blackrock.

What impressive have they done? Well, the email campaign that they ran has as many as 6912 variations.

Keep reading to understand what did they do.

The WebEngage Effect

An effective email personalization requires the combination of two important things.

Data

Okay, I am being Captain Obvious here but I still wanted to reiterate the need of data in context of personalization.

In 2018, Data is an ambiguous word having as many meanings as the word ‘cool’. So let me breakdown the kind of data do we require for effective email personalization?

  • User’s profile– attributes like name email, age and demographics
  • User events– actions done by the user on the app, web and communication channels. Essentially, when crafting an email campaign you should be able to make rules based on how user acted on certain browser push campaign you had earlier sent.
  • Screen data– data available on current page being browsed by the user. Mostly applicable when you are running real-time campaigns like Onsite notification.
  • Third party data– data stored in external CRM or anything which you should be able to fetch via Webhooks or API.

Having said that, for an effective email personalization we need to have the above data types at our disposal.

What do we need next?

Ability to add logical expressions in the email template

Add the ‘variable name’ and the corresponding ‘placeholder’- that’s the extent of the personalization that most email vendors are currently capable of. (and even marketers. No offence)

{firstname,fallback=Bruce Wayne}

But unless one cannot play with the tokens by adding logical expression in the email template, he shouldn’t even be allowed to say “email personalization”.

Take a look at your existing email tool and answer if you could do the following things:

  1. Add If/else conditions To test the presence or absence of some data and initiate an action accordingly. As in

    Input
    Subject: Hi there,

     if (user==’paid’) print(“You are awesome”); else print(“Beer money is running out. Please pay soon.”);
    

    Output

  2. Run ‘for’ loopsTo iterate a certain HTML tag, condition or anything a certain number of times. The is really useful when we want to display a dynamic list in your email which is quite often.

    For instance, see what Coverfox did.

    Coverfox, an insurance aggregator, sends the following email to the users post their search on the website when it doesn’t amount to purchase.

    The insurances in this list are dynamically generated based on user’s search history. The insurances listed here are the top search results that user got when he searched for one.

    Coverfox guys ran a ‘for’ loop on the search results and showed the top three. Needless to say, the result would be unique for every user and so would be the email.

    {% for key in event.custom['bike_quote_results_viewed'].json_data['quote_results'] %}
  3. Filters such as abs, urlencode, round etc
    Input

    
    abs(123.123)
    

    Output

    
    abs(123)
    

    Can you add ‘filters’ in your email template in the current email editor?

Essentially I am just picking the templating features from Nunjucks documentation here. You can view the full list and figure out the capabilities for yourself.

If you could do all the things mentioned above like DSP Blackrock guys can, then kudos and more power to you.

What folks at DSP Blackrock did?

The objective of the email was to send the new year greeting to customers, but tad differently from how others do. They basically leveraged the transaction history of customers to send a personalized summary of good (and not-so-good) decisions that the customer made over the year.

The content of the email was dynamically decided based on the user’s data.

Here is the step-by-step description of what they did:

    1. They divided the whole template into HTML blocks

Click to enlarge

  1. Thereafter, they created a logic sheet which defined rules for what block should be shown to what guy.So each block is to be decided on the basis of user’s attribute. How the conditions played out can be understood with the simple flowchart as shown below:
  2. Then comes the execution part. They wrote the expressions inside their HTML code which displayed blocks according to the user’s attribute.For instance, here is how the ‘if’ condition played out in the context of DSP BLackrock’s email
    
    {% if has_account === true %}
                            <tr id="box1"></tr>
    {% else %}
                            <tr id="box2" > </tr>
    
    

If we follow the actual campaign’s logic sheet then we would find that it had as many as 6912 variations.

The Result

Below is snippet of the result of the campaign. Remember, the number of their contacts runs in several hundreds of thousands.

Open rate- 39%

CTOR- 9%

Personalized nurturing of all users

Financial services market is extensively cluttered. There is a knowledge gap among investors about the various options and even, how their own fund is performing. One of the primary objectives of the digital arm of such companies is to keep nurturing the customers. Cross-selling is a big opportunity and this email aims to accomplish the same.

Having said that, the above campaign, apart from garnering the aforementioned results, most of all acquainted us the limitless possibilities in personalization once you have the data in place. We are pushing the envelope with other clients in the context of personalization. (will hopefully publish a new case-study soon)

Let us know what do you think of this methodology discussed in this post in the comments.

Like to rate this post ?
Total Rating : 19 , Average Rating : 4.4
  • Shekhar

    Hi,

    I really liked the article and got to know the actual meaning of a personalized email. Thank you for that.

    The one thing that I am curious about is how would this type of email compare to a semi personalized email, which captures only first name. Also, how would you account the 39% open rate (which is awesome btw) to the personalisation of the email? What is the avg. open rate of non personalized emails?

    Look forward to your response.

    Thanks,
    Shekhar

    • Hi Shekhar,
      “How do you account the 39% open rate to the personalization of the email?”

      Well, open rate is function of subject line copy among other variables like brand equity, context, frequency etc. We are not attributing the 39% open rate to personalisation.

      9% CTOR is actually the indicator of the campaign’s personalisation success.

      But beyond all this, the ability to create such degree of personalization is what we have tried to highlight in this post. As for the “avg. open rate of non personalized emails”, unfortunately we don’t have data on this.

      Thanks