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Force24

6 killer marketing metrics that really matter

By Adam Oldfield, MD of Force24

The life of a digital marketer is rarely straightforward. Whilst other communicators may perhaps argue it’s easier for their digital peers to evidence ROI, those within the world of email marketing, for instance, may be quick to defend their position.

Because yes, they have a wealth of metrics at their fingertips, but it can be difficult to know where to start.

Rather than focusing on what is arguable a vanity metric – like a click rate or, even worse, an email open – it’s important that marketers look deeper at the data to offer a true bottom line impact.

Insight relating to a brand’s data subjects, list segmentation, and the evolution of those segments, will help a marketer to understand what excites people and drives them to engage. Instead of asset-based reporting, professionals should therefore be concentrating on audience reporting, to assess campaign performance through a user’s eyes.

But how do marketing departments get these bottom up metrics that matter?

  1. Segments are key

Not exactly a metric in itself, but the data that matters can’t be uncovered until segments have been built to see how they are performing, how they’re growing (or shrinking) over time, and what the average lead score is. The more segments created – the better. Automation should make this possible in only a few easy clicks.

  1. Lead score matters the most

‘Lead scoring matters only for B2B marketers’ is a huge myth! Savvy lead scoring takes ALL engagement from any type of user. A points-system should be set so it can be tallied and a pre-defined ‘tipping point’ – tailored to the brand – should trigger when to act. Lead scores help to decide exactly who to focus on at any given time.

  1. Analyse average lead scores per segment

The average lead score of a segment may peak and trough over time. This data can be used to draw engagement curves that indicate seasonality, optimum purchase times, crucial cross-sell periods and when an existing customer is most likely to re-book/buy. This type of analysis also helps to quickly identify strong or weak segments within a data set. It also helps draw correlations between lead scores and campaigns, web activity and, most importantly, the number of leads actually secured. 

  1. Segment evolution

It is important to understand how a list is growing or shrinking – is the data in a segment diminishing, for example? And what might this mean? 

  1. User web engagement

We know browsing behaviour gives us a deeper insight into a user’s interests and needs, but only one in six organisations use it effectively. Web collateral should therefore be designed to support this information gathering, and engagement across this online real-estate should be analysed.

  1. User marketing preferences

It’s just as important to understand what your segment does NOT want to see – you’ll be surprised by the level of variation between data sets.