Are Platform Metrics Making Marketers Happy?
September 20, 2018
Demonstrating a revenue-based performance model in B2B requires both an advanced infrastructure on the client side and a wealth of knowledge on the agency side. There is no one-size-fits-all approach when tracking performance to revenue. Often the product or service can have a fluid pricing structure and some leads can take months or even years to close.
Operating an ROI model in B2B has three main challenges:
- Attribution and tracking
- CRM integration
- Lead Cycle
In this post, we'll touch on all three challenges but focus mainly on Lead Cycle — and explore how to deep optimize activity through pipeline.
What are the challenges in demonstrating ROI on LinkedIn advertising campaigns?
To be able to demonstrate return on investment in B2B, when deal cycles vary in size and lengths, advertisers must connect channel performance with revenue and lead data from a CRM. To do this, the advertiser must set up a parameter tracking infrastructure (e.g., UTMs) that detail as much as possible about the campaign, audience, targeting, and ad creative. This can then be tracked right through to the deals that are closing in a CRM.
Ideally, the CRM maintains a number of different lead stages to help understand what audiences, what targeting, and what creative drive leads through the funnel the quickest. In this fashion, a CRM system can help you reach the best understanding of what is performing — even before a deal has closed. The more qualified the audience is, the more likely they will be to move to complete the transaction.
One of the biggest challenges in B2B is understanding the value of leads in the open pipeline. We encourage clients to build a model that assigns a revenue-based value to each lead stage. This approach helps us project revenue before a deal has closed. Optimizing around ROI is incredibly valuable, because it accelerates decision making and improves performance much more so than optimizing around platform leads and metrics.
Equally, by adopting this model, it allows us to understand the leads that are not flowing through the pipeline. We can then minimize the waste from campaigns driving false positive conversions.
Does this approach work across all placement formats and audiences?
For lead gen ads in LinkedIn we have used CRM data to track which campaigns are sending high quality leads — the ones that are moving down funnel and driving closed/won deals.
Does the targeting impact performance?
The advantage that LinkedIn holds over other media is the ability to target a combination of parameters at the same time — down to individual job title, seniority, company, and others. One key setting that has helped improve our conversion rate of click to form completion is to optimize toward form completions.
On top of attributing LinkedIn advertising spend directly to return on advertising spend (ROAS), another advantage of connecting your LinkedIn campaign to a CRM system is the ability to export all converting emails (and perform lead scoring for high and low quality leads). From this data, you can then identify the audience or audiences to exclude on the platform. At the same time, you can also create a lookalike audience of users most likely to convert.
You’ve talked a lot about targeting people, can you also target companies on LinkedIn?
Using account-based marketing (ABM) targeting has worked particularly well for our clients, and we usually test the targeted companies against any custom matched lists available. We use an ABM strategy to target based on companies, industries, or named competitors in the industry. Other social platforms have proven limited in the ABM form of targeting. These other platforms have driven a high volume of leads — but with very few of these leads progressing down funnel.
Can you give us an example of the ABM approach in action?
Client Example No. 1: For Snag, an end-to-end recruiting experience for businesses, optimizing toward lead quality in the backend has made a large difference. After running several lead generation campaigns to custom matched and platform targeted audiences, we were optimizing around form completion volume. We were also testing as many ad formats as possible with Video Ads, which resulted in an improvement worthy of a LinkedIn Case Study. When another social channel was simply feeding MQL volume and not quality down-funnel conversions, we decided to audit the quality of the MQLs instead of simply sending volume.
With LinkedIn, we used the advanced platform targeting filters to increase the lead revenue potential. Down funnel click to SAO (sales accepted opportunity, which is when the lead reaches “down funnel”) conversion rate was 144% higher (0.06% compared to 0.14%) on LinkedIn than another social media platform after optimizing deep funnel metrics. Even when isolating LinkedIn month over month, (just ten days into the second month) after lead quality optimizations, the click to SAO conversion rate was 231% higher (from 0.09% to 0.31%) than the previous month. It may have a higher CPL on the surface, but the quality of the lead far outweighs volume in almost every circumstance. The biggest takeaway from this project is the huge potential of optimizing around pipeline value, not just MQL volume.
What about a combination of platform and back-end specific scenarios? Does this approach still work?
Client Example No. 2: For our client Genesys, a leader in both cloud and on-premise customer experience solutions, we leveraged a combined approach. We put together LinkedIn’s powerful targeting functionality with the platform's Lead Gen Forms. This combination is another example of how LinkedIn has driven huge opportunity and positive ROI for one of our clients. Using an ABM strategy, we layered enterprise accounts on top of criteria such as job functions and seniority to reach key decision makers within key target companies.
We launched a campaign A/B testing lead gen forms against sending users to a gated landing page on the client’s site. LinkedIn’s in-platform conversion tracking provided valuable insight into the performance of the test, which showed a 147% higher conversion rate with Lead Gen Forms, and a 59% lower cost per lead.
However, this was only the start. By combining the data within LinkedIn and the client’s CRM, we were able to attribute the generated pipeline back to our campaign, which achieved a projected 74x ROAS. Combining different data sources, in this case LinkedIn and a CRM, can paint a much clearer picture as to what’s actually going to drive return from your media campaigns. Optimizing at a platform level will allow marketers to drive more conversions within their budget, and gaining insight into how your leads perform further down the funnel will allow you to optimize your campaigns to revenue.
Any closing advice you’d give to companies using LinkedIn?
LinkedIn offers value in its platform and the leads it can send your business. Those results can be easy to demonstrate. But there is so much more to the equation on the back end. For a maximum amount of success like the scenarios I described above, stress the importance of setting up CRM integration and sales funnel metrics to optimize around performance. This will take a good amount of planning, the right account structure, and strategy, but will go a long way in the eyes of your client.
To get started on your own LinkedIn advertising campaign, visit LinkedIn Campaign Manager today.