How to realize value from Marketing Automation in 2023 - Part 1

2023 is not far away - so if you want to ensure a marketing automation initiative creates value next year you should be planning for it now.?

In your planning, there are a number of things to consider. Prioritizing integrations and enrichments, identifying new channels and touchpoints, aligning stakeholders on full-funnel experience optimization, determining an attribution approach, etc.

However, all of those strategic elements can only realize value if you are also planning for something else: User adoption and upskilling.?

Automation is meant to bring value by releasing your team from repetitive manual tasks to focus on higher value activities. So to ensure you get value from marketing automation in 2023 you likely can’t afford to invest in a whole new team of Marketing Operations specialists. You need to empower your existing marketing team and augment with new resources only where necessary.?

The challenge is, even if they have been using marketing automation platforms already, your team may not have the skillset needed to succeed as you embark on the next phase of your automation journey.

Fortunately, automation in this context is not rocket science. A condition is met that triggers an action which uses relationships to complete its tasks - and possibly triggers additional actions.

For example, a new customer enters your database which triggers an onboarding email that can use relationships in your database to personalize the email content with details of the customer’s purchase. Simply sending the email might trigger next actions, or you might set those based on whether the customer interacts with the email - thereby meeting a new condition.

So what’s the disconnect?

The Data Model Disconnect

When I meet with marketers who are frustrated by a lack of value from their current marketing automation systems, a common theme is that they start from a position where list pulls have been enabled by another team - often a BI team.

To maximize value, an automation initiative will be planned so that the marketing team will now be able to pull their own lists - or (better) be able to create logic that will dynamically put customers into a list when they meet a set of conditions (a “segment”) - or (even better) be able to capture real-time and multi-channel customer interactions and use them to trigger 1:1 communications (aka “journey orchestration”).

In that scenario the biggest challenge for the team is learning the data model that the BI team has been managing for them.?

Your team may have been using email lists or segments for years. However, they may only know them by name, or only have a conceptual definition of them, with no idea which conditions are used to create them or where those conditions come from.

In fact, I’ve spoken with several marketers who found that nobody in their organization knew how the target audience for an email is generated - as the BI process was created by someone who has since left the organization and didn’t share documentation. I’ve even heard from teams that don’t know what application sends some of their emails!

If that sounds like your team, don’t worry. It’s more common than you would think.

However - do act on it. And do that as a first priority.

You should not embark on a new marketing automation initiative if your team does not know your data model. Not knowing can lead you to make the wrong platform selection, or the wrong integration and enrichment provider decisions. It can certainly lead to new applications being configured incorrectly.

Even if that worst case doesn’t happen, a team that doesn’t know their data model will not be able to achieve value from the enhanced technology - because automation is all about acting on the conditions and relationships in your data model.

Selecting the audience for a communication and enabling personalization within it should get more granular as you aim for “segments of one”. This includes both linking to data from additional databases and respecting consent and preference, whether known or implied.

If your team doesn’t know your data model they probably won’t have actionable ideas on how to generate more contextual offers and experiences and they definitely won’t have the confidence to implement them.

That sets the problem - but what’s the solution?

Dynamic Knowledge Transfer with Design Thinking

I’ve shared the challenges - but the upside is that the marketing teams I have met with want to learn and want to provide exceptional customer experiences.

Your people are your best asset - but you have to enable them via collaboration and dynamic knowledge transfer.

Traditional knowledge transfer would include things like an entity relationship diagram and a data dictionary. These are still necessary but should only be the starting point.

A great way to engage in dynamic knowledge transfer is via Design thinking sessions; where you bring a group of people with diverse roles and skill sets together (eg your BI team and your Marketing team) to collaboratively gain empathy with a situation, define the components parts of it, and ideate how to address them.

Let’s take that onboarding email series as an example. Maybe you already send an email offering 20% off a recommended next product 2 days after the customer clicks on their welcome email. But is that what the customer wants?

What if they haven’t received their initial purchase item? What if they have sent it back? Or expressed a preference for a different product online?

If you want to suppress or change the offer in those circumstances where would you identify the necessary conditions in your data model?

Those sessions might extend to an individual prototype, tested with a control group. You’ll get most value though, by extending those initial sessions to an ongoing Innovation and Prototyping workstream. Engaging in hackathons, agile experiments, proof of concepts and pilots. The small (two pizza) team in that workstream will also come up with other ideas for automation beyond your data model - like automating approval workflows, integrating asset stores etc.

This team can be further extended to your center of excellence. This should be a group of cross-functional subject matter experts continually evaluating how to productionalize innovations. This includes your “train the trainer” leads - who bring cross functional knowledge and experience back to their departments.

Next Steps

If that sounds like a lot to take on - don’t worry. Avanade can help. We have design thinking experts, and established methods for turning the ideation into proof of concepts and pilots alongside your teams.

Feel free to reach out if you would like to learn more. And look out for the next article in the series, where I will cover the strategic considerations you can tackle once you have the foundation of user upskilling to ensure adoption.?