Bridging the Reporting Gap

You've just launched your spectacular new campaign. Engagement is high, leads are flowing like water and the pipeline is bursting with new opportunities. Now comes the discussion about reporting. Decisions need to be made about what numbers to show the business, how to present them and the story to put behind them. You have a campaign code and UTM tracking, so no problem. At least that's how it's supposed to work. The reality tends to be far different. Getting coherent end to end reporting always seems to be the hardest part of any campaign.

If you struggle with getting comprehensive reporting, start by checking if you have the right campaign codes and source tracking. Far too many marketers create one campaign code for the entire campaign and then run into trouble attributing leads to individual tactics further down the line. This is because campaign codes are typically designed to do two different and potentially contradictory things. They are mainly a mechanism for attribution - for reporting which leads came from which campaign so that ROI reporting further down the line accurately shows marketing's contribution to the bottom line. Business and Sales leadership typically only care about this at a high level, so campaign codes are high level to match. Granular campaign codes often get pushback from Sales teams who use them to make decisions about how to follow up MQLs. They find too detailed campaign codes a confusing chore, and would rather not have to deal with them.

The conflict is that marketing want highly granular campaign codes so they can report on the success of every tactic individually. Marketing managers expect full funnel views, so they can see the status of every stage of the campaign and analyse results to inform the next one. Multi-level campaign hierarchies solve part of this problem. This approach allows the creation of parent and child campaigns, enabling the creation of more granular tactic or channel level codes that roll up into an overall campaign code for executive reporting. The one limitation of this approach is that these hierarchies only exist in CRM, so give a small part of the picture.

The Data Gap

When talking about attribution, restricting yourself to looking at leads attached to a campaign record in CRM is generally considered to be a good starting point. If your systems are configured according to best practice, any high value activity tracked by a marketing platform is added as a campaign response against the relevant campaign. If someone responds to enough campaigns they become a lead and get included in attribution reporting along with all the campaign responses logged against their record in CRM.

This would be fine if all your marketing activity took place in sites and platforms that track every click or conversation back to a named individual in your CRM or your Marketing Automation. In the real world, nobody has that luxury. At least 50% of the buyer's journey takes place before you even know who the buyer is, and that number is going up not down. Sure, Google knows the names of the people hitting your website from search and PPC, but they're not sharing that with you, the same goes for the social networks. The majority of your website visitors are not linked back to known MA contacts until they fill in a form, which few people do.

Campaign code based attribution misses out on all this activity because it takes place outside of your CRM and Marketing Automation platforms. Marketo and Eloqua only have information about known visitors linked to a contact in their database. What they do not have is any information about the overwhelming majority of website visits that are tracked in your Web analytics. Sure, your MA system might have anonymous website history, but it can't be used for reporting on inbound traffic. The net effect of this is that all this critically important website traffic ends up being left out of any funnel reporting, as well as any buyer's journey analysis. No one knows whether it actually contributed to a purchase because no one how the people visiting the site actually are.

The Next Generation of Tools

This reporting gap has given rise to a new generation of attribution focused reporting tools that can show lead volumes, funnel velocity and revenue contribution at every stage or level. The most prominent of these is Bizible, who are now part of Marketo. They eliminate campaign codes entirely and pull all your data into a giant funnel dashboard with extensive drill down options. To get this to work, Bizible integrates with your entire tech stack from CRM through Marketing Automation and on to your website and Content platforms. This also have direct integrations with all the major ad platforms and social networks so they can extract page views, clicks and impressions to give the full picture. This is a revolutionary capability which exposes how little of the funnel Marketers have visibility of using traditional methods. Your BAU LinkedIn and Twitter updates all have an impact but are often ignored in attribution reporting because you don't have information on who is viewing what. Bizible claim to have that detail, and to be capable of linking it with opportunity data to prove ROI.

Doing this reminds marketers that campaigns are not the only way to measure business results. The board is often more interested in the impact of marketing on the revenues of specific business units or product streams, while marketing leaders care more about the results of themes and tactics than individual activities. Campaigns are a budgeting and planning construct intended to group a related set of tactics into a coherent message with a clear journey. You think in terms of campaigns, but your audience does not. They only see the brand and the content across the channels they're using. In doing this, they align much better with the Bizible way of viewing the world than the traditional one.

The Importance of Interpretation

Individual campaigns are still relevant and for a good reason. The key is to remember why. When looking at campaign results, you are actually looking at the impact that specific messaging, design and channels are having on your pipeline. It can be difficult to interpret which of these three factors is causing success or failure for particular cases, but interpretation is generally focused on deciding the effects of individual campaign elements in these areas. Grouping related campaigns together adds clarity by allowing trends to be observed. Traditional reporting frameworks do enable this by using campaign fields to record the channel, themes and business units of the campaign. Campaign roll-up reporting is then used to draw comparisons. Such reports are critical when trying to interpret results and discover learnings, yet many marketers don't do enough of them. When doing roll-ups, remember that you need to consider the full picture, and that doesn't exist solely in your CRM system or only in your web analytics. A holistic view requires pulling all the various lead activity data sources into one location so that you can see the end to end impact of specific activities. Bizible can do this, but so can a data analyst in a BI tool if you have enough time and money. Bizible's advantage is they do all the work in getting that data for you. However, to get the most out of it, you need to be running a high level of activity across a wide range of channels otherwise you don't get the full benefit of their dashboards. Bizible can then empower you to map user journeys and spot trends in a way that the typical CMO dashboard can't match.

The guiding principle behind robust reporting is that getting the right information is necessary but not sufficient. It's important not just to have all the relevant reporting data, you need to be able to analyse it and use it effectively. If you're relying on offline formats for your reporting, then this just isn't possible. You will always be limited to what the data can show. It can't be sliced, diced and explored until you discover the insights needed to make the report relevant to you and your team. Effective reporting is based upon shaping the data to fit the narrative you want to tell, but this requires all the right data to be available in the first place. It's surprising how difficult this is to achieve, but the right tools make it easier. The challenge then becomes drawing the correct conclusions, but that's a problem for humans rather than technology to solve.