Home Data-Driven Thinking Barriers to Benchmarking, And How Agencies Can Overcome Them

Barriers to Benchmarking, And How Agencies Can Overcome Them

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“Data Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Kyle Barber, SVP Global Performance Lead at McCann Worldgroup.

While on vacation in Turkey this past week, I vacillated between aimlessly wandering the streets one day to carefully researching the possibilities the next. By looking at what others had recommended and creating some maps, I knew I would maximize what I could see in the few days I was in Istanbul.

I mention this because it highlights a prevalent danger in the agency world.  Client teams often provide campaign reporting, but sometimes go for leisurely, directionless strolls. They do not consistently use the findings and insights to guide what they will do next as a long-term client partner.

The whole practice of analytics is founded on the idea that evidence guides what to do next. Once you have identified patterns in your data set, you can hypothesize what to try in next quarter’s campaign or optimize what is happening on your site.

Requiring the use of benchmarking across all campaigns is one of the best ways to establish a useful data set. Doing so provides a palette on which the data scientist can explore his or her creative side. The most revealing data comes over time across campaigns, and setting up this benchmarking framework is crucial for long-term success.

While benchmarking is very popular with both clients and agencies, it often does not come to fruition. Why does this helpful practice get championed by stakeholders but not implemented? There could be any number of reasons, but I believe the big three are (1) adequate lead time to discuss and plan, (2) the skills and bandwidth to actually set up a consistent plan across all efforts and multiple clients, and (3) the challenge of data sharing.

Planning

When tasked with a new campaign, we’re often told the project requires fast turnaround. Strong agencies will rise to the challenge and move at a rapid clip, while also making time to ask the tough questions. Are we aligned on the business objectives? Have we documented them along with a general sense of the project’s scope? Will we use previous benchmarks to set performance goals?

At this initial stage, it can be tricky for analytics folks and strategists to get account teams and client leads to stop and evaluate the “how” and “why” along with the “what” and “when.” If internal agency teams commit to a minimum planning time for data strategy, they will not only avoid problems later but provide considerable long-term value that helps win the client’s trust.

The teams that I have most successfully partnered with at McCann are those that buy in to the process where we alot time before campaign launch to discuss strategy, including data capture and measurement. Committing to a process across all campaigns (preferably in writing to share with all team members) ensures that the proper steps are taken to set up and employ previous benchmarking for campaign design.

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Having the skills and bandwidth to set up benchmarking might seem like the greatest challenge to the outsider, but an analytics practitioner has significant control here. This hurdle has less to do with technical skill than with thoughtful analysis and strategy. What are the client’s monetary goals? What secondary objectives should be measured? What campaign-specific learnings can be rolled up into categories that inform year-end learning?

This type of thinking is what separates a report jockey from a data strategist.  We’re not in the business of generating pretty dashboards. Rather we need to provide actionable insights that shape the way our larger agency team helps the client.

When interviewing analytics candidates, I spend considerable time asking how they would approach insights generation for clients. Requiring demonstration of strategic application of the measurement insights as a year-end job performance goal ensures team members are always thinking about their charge. And committing to a data strategy partnership with clients, then soliciting regular feedback from said clients, keeps you honest on how well the overall team is following through.

Data Availability

Data sharing is the greatest hurdle to overcome, particularly as clients spend more capital on internal data resources and analysts. The water is muddied further when there are multiples agencies involved, often a group of competitors who imagine that there is a bigger slice of the pie available to them if they play their cards right.

Before one even commences a campaign, there should be some clear understanding and agreement between all parties on what is the fiscal year, or multi-year, data strategy. Be clear on why each partner can and should own their particular data set, how much of that they will share, and what the long-term usage will be in an industry where partners change frequently. If there is only one agency involved, there still needs to be clear understanding about what role the agency, client and technology providers each play with data capture, fusion and storage.

An agency of record should not only fight for the privilege to house client data, but also come to the table with unique data sources that offer added value.  While the real win for the client is the clever ways that data can be merged and normalized to create the perfect performance indicators, an exotic new data source is enticing.

Follow Kyle Barber (@kylebarber) and AdExchanger (@adexchanger) on Twitter. 

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