3 B2B Marketing Automation Observations

My as a Customers Success Director

There is no shortage of blog posts and people sharing their views on the e.g. “3 big trends” in CX, marketing automation and other related topics for 2018. My frustration is that there are few examples from the B2B world.

Given I spend 90% of my time with organisations selling to other businesses I thought I could share some of my observations. Clearly I can’t divulge specific brands and their campaigns, however I can collate my observations and summarise what I’m seeing and the changes.

1st Observation: Industry specific Lead Nurturing

Throughout 2017 a number of clients took significant steps to begin the build process for industry specific lead nurturing campaigns. The lead “generation” process came from other campaigns and would feed into the “nurturing” campaigns.

Most of these were industry specific. Clearly this involves more work, but after discussion and debate, in most cases it was agreed an industry approach was the right way to go about these campaigns.

Some additional preparation work is often needed to ensure the smooth execution of these campaigns, essentially a focus on overall data quality.

Some clients have taken their entire database, typically Account level data from the CRM, and provided it to data cleansing organisations like DCA (Database Consultants Australia) or Dunn & Bradstreet (now Illion in Australia) and others. This process returns your data with up to date account level data which will help ensure your segmentation is more specific and accurate.

2nd Observation: Personalise each interaction

In the B2C world and the case studies from that industry, personalisation is generally knowing about you in detail from a profile point of view so more products or services can be served to you.

In the B2B world, it’s probably not that different. However the way you gather the data to arrive at point where you build out a prospect profile, is quite different.

The key piece of data most B2B organisations have at their disposal is the CRM and some will also have ERP and maybe additional data sources.

If you add Eloqua’s behavioural data to this mix, you have a great deal of information available to help you:

  1. Segment your Contacts better and
  2. Personalise your campaigns with greater detail.

In the B2B world, I think it’s fair to say that people will not spend money until they have a ‘business problem’ and they won’t spend their money with you until they’re satisfied you have a solution to their business problem.

3rd Observation: Find your next campaign in your own data

After years of “Big Data”, “IoT” we really should be in a position to ‘do’ something with the array of data we have available. 

I’m starting to see customers look at their own data as the beginning point of campaigns.

It’s early days, and in some cases they take some convincing, but many are at a point where the data they have in Eloqua, married with their CRM and other data can deliver very specific audiences.

For example, using either Eloqua’s Segmentation tool or Insight analytics, it’s quite easy to uncover certain behaviours and trends.

Personally I find that segmenting the data with a range of filters helps to discover audiences that otherwise you may not have noticed.

For example, an easy segment to build in Eloqua is to have Eloqua return all Contacts who have not been sent an email within the past twelve months. Some clients insist this will be a small audience, however it’s always larger than they thought.

This is the first step to a re-activation campaign. With additional segment filters you can adjust inactive groups by profile and engagement. 

While you may not have emailed this group, you will find some amongst them have been visiting your website. There’s value in exploring what they’ve been looking at and the frequency of their visits.

This degree of segmentation could lead to trigger based campaigns. This is easily done using various filter criteria within segments, preparing your campaign and then setting Eloqua to check each day, or each hour, who meets the filter criteria and then engaging with them via automated outbound emails.


  1. Review your own data and determine how easily you could target contacts by their industry.
  2. As you devlope campaigns and copy, look at ways to personalise your communications beyond addressing people by name.
  3. Once you’ve completed the two points above, you will most likely have a better understanding of your own data. Review it closer, what’s it tell you? Think of campaigns that could take advanatge of the new insight you’ve uncovered from your own data.