Modern marketing decision-making

Making marketing decisions at enterprise scale

Decisions, and the process of making them, is an important part of the digital marketing customer lifecycle. Marketing decisioning, put simply, is the process to determine which message a customer should receive through a given channel or medium.

Many organisations take a relatively simplistic approach to decisioning and attempt to use a single platform to make decisions. This platform then pushes data to a delivery tool (or tools) for message generation and presentation.  

This works well for small organisations that have a limited set of relatively simple campaigns to decision for, and a simple set of rules for deciding which messages an individual should actually receive. This rule set is commonly known as a contact framework.  

In these simple cases the decisioning platform can also be the delivery platform. However, in most large enterprises, the decisioning process and contact framework is far from simple. 

The single-platform decisioning approach does not scale to larger organisations that communicate through multiple channels, with a large set of campaigns and a complex contact framework.  

In large enterprises, there are typically three different types of decisioning that influence marketing campaign delivery:

  • Campaign Decisioning (also known as customer targeting and personalisation) determines which contacts should be targeted by a given campaign and generates personalised data to populate that campaign.

  • Message Decisioning: this is where the actual message or offer that a customer should receive is determined. This is particularly important for multi-step campaigns, where a contact may receive several different messages based upon custom logic and data.

  • Contact Decisioning: when a contact is a candidate to receive multiple messages or offers in the same time window, this is the process that determines how many of these messages the contact will actually be presented, based upon a prioritisation and/or suppression framework. 

Although each of these types of decision is distinct and relevant to a different stage of the campaign journey, many large enterprises do not split out decisioning into distinct stages. A key reason for this is that large organisations tend to centralise processing - because it generates a sense of control and makes it easier to trace what processing has occurred.

An outcome of adopting a centralised decisioning approach is the provisioning of large platforms and associated infrastructure to perform marketing data processing. Also, under this approach, delivery and presentation platforms perform no decisioning and are only responsible for message rendering and/or delivery.  

Unfortunately for enterprise marketers, a centralised decisioning approach has a number of key issues that result in poor marketing outcomes:

  • Long campaign turnaround times due to complex campaign setup and the significant operator expertise required. 

  • Under-utilised capability of marketing delivery platforms, resulting in campaign experience being less ‘rich’ and engaging than what is potentially possible. In a centralised decisioning approach, the maximum level of experience that can be delivered is limited by what the decisioning platform can do, not by what the delivery platforms can achieve.

  • High cost of change as all contact rules and decisioning logic are centralised in a single enterprise-wide platform. 

  • Confusion and complexity as decisioning is merged into a single process without distinct stages and separation of concerns. Complex decisioning configuration in a single platform leads to a lack of clarity within the enterprise as to what the contact rules are and the impacts that they have.  

Of course, the main reason for the friction between a typical enterprise IT-led approach and an ideal marketing approach is the appetite for change. Marketers need to be inherently flexible and reactive to match changing consumer needs, while IT managers are driven by needs to centralise operations, control costs, and reduce the need for change.

The ideal enterprise approach to decisioning

To achieve a winning balance between the needs of marketers and IT managers, enterprises need to focus upon developing a decisioning capability that can provide all of the following:

  • Fast campaign turnaround times to meet changing customer needs and mitigate against competitor activity.

  • Reduction in the need to engage costly IT resources to deploy marketing campaigns.

  • An environment where test and learn approach can be adopted, enabling marketers to optimise campaigns based upon performance.

In this approach, decisioning is not centralised in a single platform – rather it is divided between platforms that have capabilities best suited to perform each type of decisioning and for the type of operator that will be driving it.  

  • Campaign decisioning in a Customer Data Platform or dedicated decisioning platform that delivers a set of campaign independent records per contact with targeting flags and personalisation.

  • Message decisioning in a marketing platform that includes journey building capability. This delivers fully personalised messages for delivery to contacts for the given time window.

  • Contact decisioning in a marketing platform with contact framework capability that allows for the delivery of prioritised and personalised massages to contacts.

A key advantage of this approach is that it does not require any specialist IT or development resource to design, decision and deploy campaigns, instead using existing marketing and data analyst resources more effectively.

This approach also allows marketers to utilise the full capabilities of modern multi-channel marketing platforms to build out complex and rich customer experiences. Having the contact framework closer to the point of delivery also allows alternative models to be generated and evaluated as all of the potential messages are available for review.

Adopting a decentralised decisioning approach for marketing does not mean increasing complexity or adding additional cost. In reality, done well, it is a ‘fit for purpose’ approach that utilises existing resources and technology better without impacting the integrity of the enterprise data framework.

n3 Hub enables marketers to automate the decisioning process across the three key types of decisioning, and can be deployed quickly with minimal impacts upon existing IT infrastructure. For further information on the capabilities that we can bring to your marketing technology stack, please contact us.

Damian Williams