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Blog / How To Scale a Digital Marketing Agency

How To Scale a Digital Marketing Agency

In this episode of The Undiscovered Metric, we sat down with Cam Benoit, Team Leader of Solutions Consulting at Adverity to discuss how agencies can scale their data strategies to make the most out of their marketing data.

Watch the video to find out how you can scale your agency’s data pipeline

Hi Cam, could you give us a little background on your role and career?

Hi JJ, I've primarily been a solution consultant, helping folks choose the right technology and strategy for their specific scenario. I've worked on some of the largest data processing and data mining implementations in the world.

How can agencies manage all their data requirements with so many data touchpoints, and what metrics should they focus on to prove value for their clients?

Although there are a ton of new data sources, the core six or seven data sources are staying the same. With the right automation setup, agencies can reuse about 80% of what a new client needs, and then build out the remaining 20% later on. Seeking out similar clients can help agencies grow quickly and future-proof their business. 

 


Check out our agency guide to data storytelling!


 

What are the key data questions that clients should be asking about their data on a regular basis?

There are a few questions that agencies need to ask themselves:

1. How easy is this to change for all 200 of my clients? 

Change Management can be very time-consuming. It is like buying a boat, it's not just the upfront cost, but the maintenance costs that come with it every year, if you see that cost as time, you immediately see the need for automation.

2. How easy is it to add a new client to this pipeline? 

It can be very easy but you need to look at techniques such as cloning. What can be cloned and reused without having to rebuild the same thing? All software is written in code and this is absolutely something that can and should be done everywhere.

3. What does my team spend their time doing?

It absolutely should not be maintaining current processes, it should be thinking of the new and best way to do things, then automating that so you can have that every day.

4. Where is the root of the problem in the real world? 

How can I find some information somewhere to really add color to the data story we are trying to uncover? Solving this can require blending some data from several sources or manually adding in some elements to really give the data context.

5. Does this all still work if I am doing it for the largest real-world use cases?

You don't know if something breaks until you actually test it out. I don't love the phrase “kick the tires”, sometimes you have to just have to take the Mustang to the race track to make sure it can beat all of your friends.

How can agencies get around the challenge of naming conventions for different data sources?

Schema mapping can help agencies deal with different naming conventions. By creating a standardized naming convention that everyone understands, agencies can ensure consistency across different data sources. It's also essential to have a good understanding of each data source and the specific metrics it offers to make sure that everything is labeled correctly.

How do you see data changing the way agencies work, and what's your outlook for the future of data-driven marketing agencies?

As data becomes more accessible, agencies can focus on providing clients with actionable insights that can help them make better decisions. In the future, we can expect data to continue to grow in importance, leading to more data-driven marketing agencies that help clients achieve their ultimate business goals and KPIs.

What advice would you give to agencies looking to scale their data strategy?

There are four key things that any agency should be looking at in my opinion:

  1. Investing in the right technology and processes to automate your data pipelines. 
  2. Seeking out similar clients and reusing existing processes to save time and effort. 
  3. Looking for new dimensions in your data to gain deeper insights and move beyond high-level vanity metrics.
  4. Making sure you have a standardized naming convention that everyone understands to ensure consistency across all data sources.


Do you think businesses sometimes fail to consider core business objectives before building a data strategy?

 

Absolutely. The end consumer should really be someone that understands the limitations of what data infrastructure can be built, and what they currently have. They need to have ongoing conversations with the people building the dashboards and providing constant feedback.

What's nice about using some of the no-code tools that are available today, or working more directly with the engineers when you need to do more of those deep dives into the really technical stuff is that it helps improve the status quo and helps future-proof the project for when other requirements come in later down the line.

What would you say is the most undervalued metric and why?

The most important metrics usually tend to be the complicated ones that customers find and ask you for in the middle of a project, rather than the top-level metrics set out at the beginning of a project.

It's important to be prepared when automating your pipelines so you can work on these little side quests that folks always think of. Each client will have one that is most important to them more so than just CTR (Click Through Rate) for example.

How can agencies build reports that lead their clients to actionable insights?

Instead of just putting a filter on a dashboard, what you can do is break the data out where it's already a little bit pre-filtered. If you are looking at Click through rate as one number, your doing it wrong. You want to use dimensions to divide up the data in as many ways as possible to see where exactly a specific trend is coming from.

Maybe CTR is down, but only for one campaign. So, you want to identify two or three top-level metrics that you want to focus on and then group them, and then you can drill into those later on. That way you get a clearer picture of performance and it makes insights more valuable.

Is there anything else you think our audience should know about scaling a data-driven marketing agency?

When you're working with the right tools and you've thought about the business objectives, you can achieve a lot.

The idea of manual processing is something that we really need to leave behind. The best thing about automation is that you can guarantee to teams that the data is accurate and up to date before teams even wake up, saving huge amounts of time and money, and decreasing the risk of human error.

"Simply put, scaling a marketing agency is about automation, and it requires a deep understanding of the core business objectives, relevant and actionable metrics, and the right tools to automate the process."

Cam Benoit, Team Leader of Solutions Consulting at Adverity

 

What are the things that you think are really going to catch fire over the next 18 months?

One trend that's really catching on right now is the use of auto-generated content, such as with ChatGPT. I think this trend is only going to grow in popularity, and agencies that aren’t using these types of tools will be missing out and will be less competitive.

As we automate more and more of the content creation process, we also need to be automating the tracking of how these campaigns are doing. We need to be able to understand how ChatGPT-assisted campaigns are performing compared to those created by normal content writers. So while automated inputs are great, we need to ensure that we're tracking their effectiveness too.

What other trends do you see emerging in the future of marketing?

I think good old-fashioned organic marketing is something that a lot of brands haven't fully dove into yet. If you can be the encyclopedia of your industry, providing valuable content and educational resources on your website, you can really set yourself apart from the competition. This type of organic marketing is incredibly cost-effective, and it allows you to utilize all the talent within your organization to its fullest potential.

With all these different trends emerging, what's the key takeaway for agencies looking to scale their data strategies?

The key takeaway is to focus on delivering value to your clients. As we move away from traditional paid advertising, and towards more organic and influencer-driven campaigns, it's essential to ensure that you're providing real value to your audience. By focusing on delivering quality content, building strong relationships with your clients, and leveraging the latest technologies, you can ensure that your agency stays ahead of the curve and continues to deliver great results.

 


If you enjoyed The Undiscovered Metric, you can check out the previous episode here.

Sinem Soydar Gunal, Senior Digital Marketing Manager at Vodafone, discusses how Vodafone has introduced multi-layered metric reporting, and why data truly is a global language.

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