How To Take A Data-Driven Approach To Demand Gen Campaigns

When it comes to delivering a successful demand generation campaign, data and measurement are critical. While this should go without saying, it’s amazing how many companies still conduct their marketing without any clear visibility on their performance. Without access to the right metrics, marketing activity can’t be justified, evaluated or improved.

Just consider that for a second:

You want to provide accountability for your marketing spend

You can’t.

You want to identify what went well…

You can’t.

You want to evolve to deliver better results next time…

You can’t.

I think you probably get the picture by now – measurement is a key component and it can’t be treated as an afterthought.

With that said, collecting, analyzing and acting upon performance data isn’t always simple. With so many pieces in play, understanding what is and isn’t working is critical to making reporting results actionable. Remember, collecting information is pointless unless it’s going to be used!

To embrace a data-driven approach in your demand generation campaigns, you need to take a methodical approach. The simplest way is to break down your approach into 4 stages; Discovery, Design, Deploy and Optimize.


The Discovery Stage

At the Discovery Stage, you should be focusing on what it is you’re trying to achieve and then identifying the metrics that influence that objective. So for example, take the likes of prospect conversions, cost per click (CPC) and return on investment (ROI), these are all different marketing metrics that offer highly valuable insight for various objectives within a demand generation campaign. Each will have varying importance based on the tactics and objectives within the said campaign and will require relevant prioritization as a result. In some campaigns, ROI may be irrelevant (unusual, but does happen), in others, prospect conversion rates won’t matter. It really all comes down to the objective.

For example, if you are looking to sell an exfoliator, then your campaign should consider the target audience, and then come up with the right metrics.

Unfortunately, many companies focus on the wrong metrics when it comes to measuring performance. They have the right mindset, but get lost in vanity metrics that don’t actually make all that much difference to the results that impact their objective.

For example, instead of looking at conversion rates on an asset landing page, they’ll look at the number of people arriving to the page. This creates a disconnect between the figures and the desired results. These vanity metrics look great on paper but aren’t indicative of success or failure, so don’t really offer a lot in the way of insight.

The Discovery Stage should be where you identify what metrics matter, the role they play in achieving your objective and why.


The Design Stage

Once the key metrics have been identified, you need to determine how they can be monitored and measured, and this is where the Design Stage kicks in.

Just because you know what data you want to focus on, it doesn’t mean you can effectively access that information. You need to think about what systems you have and whether they integrate well to provide accurate data?

In addition, you need to know if there are silos that prevent you from seeing the full picture. These are all factors that have to be considered carefully as you build your data-driven approach.

You can’t afford to be working from only a partial view on key data, particularly if that information is going to be used to guide future decision making.

In order to get the big picture, technology not only needs to be compatible but also effectively interlink together to ensure there are no anomalies that impact the validity of the data. Designing a system that gives you a full view of critical information is essential to taking a data-driven approach to your demand generation campaigns.


The Deploy Stage

With objectives identified and a clear understanding of how data management will work, you need to move onto the Deploy Stage. This is all about the practicalities of building the system that’s been designed.

You already have an idea of the information you want, why and how it will deliver value and now you need the technology and systems in place to ensure that information is easy to access.

Many companies underestimate how challenging this can actually be. Few consider the limitations of their legacy tech stack and many often struggle to take the right steps to overcome challenges.

Often it will require custom APIs, enabling systems to play nicely together. This is where the interconnected nature of demand generation campaigns can make measurement challenging.

Beyond achieving data accuracy, the Deploy Stage is also where you need to think about how data will be collected and visualized. Will it be gathered automatically in a centralized location or will each piece need to be manually collected? These are considerations that require further thought based on the needs and complexity of the project.


The Optimize Stage

At this final stage, your objectives are clear, your system is designed and built with the relevant data collection capabilities and integrations. Now, it’s about analyzing and using that data, and this is what the Optimize Stage is all about. In this stage, you will be reviewing your key performance metrics and developing actionable conclusions.

This may involve trend analysis, or focus more on recognizing anomalies, it really depends on the metric and the objective. Whatever the case, the outcomes of any evaluation should be actionable and designed specifically to improve future campaign performance.

Some demand generation campaigns fall down due to the failure of a single component and so optimization really is key. If one metric in particular is undermining the rest of a campaign, this stage can turn a struggling project into a powerhouse.

With the ability to A/B test most changes, it’s easy for iterations to be made and trialed with a small test audience before deploying them across the entire campaign. This not only helps to maximize the impact of changes, but encourages experimentation with alternative approaches.


Driving your demand generation campaigns with data

Running a successful demand generation campaign can be tricky, but with a data-driven approach, companies can quickly identify what works and why. This helps to build fully justified campaigns that can be iterated upon to drive performance and ROI.

With the right data points to hand, at the right time and in the right format, campaign performance can be reviewed in real-time, unlocking the opportunity for regular changes and improvements.

Data can turn your demand generation campaigns into ‘live’ assets that adapt as and when required to achieve their objectives. This ensures every component is working to its full potential and delivering the necessary results to drive the metrics that really matter. Using the ‘Discover, Design, Optimize, Deploy’ model you can take your first steps to achieve a data-driven approach in your demand generation campaigns.

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