Research & Analytics
We help you prove and improve the value of your marketing with advanced analytics,
insights and predictive capabilities.
There should be three primary purposes for investing in marketing analytics:
- To make informed decisions around the direction of your marketing strategy
This means taking analytics from particular channel and using those insights to inform other marketing decisions including, where to spend time, effort and marketing dollars, or how to tweak products, technology platforms or marketing offers for better results.
- To automate marketing decisions and reduce human insight error
The adoption of marketing automation technology is expected to increase by 50% by 2015. Predictive analytics in particular help to augment those very few and treasured resources in any corporate marketing team who are dedicated to running predictive analysis models around customer likelihood to purchase or churn. These can link in directly to your marketing automation tools and help to inform sales efforts in particular, where time is money.
- To provide visibility to your internal or external stakeholders
Did you know that visual data is processed 60,000 times faster than text? This provides an excellent opportunity for communicating information more effectively to key internal stakeholders. CMOs report they spend 8% of their marketing budgets on marketing analytics, and expect to increase this level in the next three years and much of this is being driven by increased expectations at a CEO or senior level to have marketing teams provide a tracked return on investment.
How It Works
We couldn’t be the type of agency we claim to be without prioritising marketing analytics as a core part of what we do. Without this, we cannot use customer insight and data to drive our decision making.
Define your needs
We look to understand your data analytics needs. This process often involves interviews with key personnel who are involved in receiving and making decisions based on data.
Visualise data output
We visualise, using wireframes, how each of those key stakeholders want to view the data. This way, you have complete clarity on what the outputs will look like.
Map current data
We investigate and speak with all key data owners, tracing your data through internal or external systems to understand data source, data integrity, data cleanliness and data centralisation.
Here, we review all information collected to date, highlight key concerns that need to be addressed for long term viability of clean data and data insights, and then provide a plan for a phased approach to set up and delivery.
Test and Learn
Before detailed build begins, we take a small component of the work to be done and test out the workflow and data output.
Analytics Build and Integrations
After incorporating learning’s from the test, we then begin our approach to drawing together and presenting all key pieces of data as per the plan.
Ongoing Insights and Support
Often there is a need for ongoing support around what the data means, if those insights cannot be gleaned automatically. Our team can provide ongoing insights based on our market expertise, while collaborating with your team for further insights based in internal knowledge.
Why We Stack Up
- We are solution agnostic, so our goal is to select the best analytics tool or set of tools based on your business requirements.
- Our team includes strategists as well as analytics, ensuring both a bottom up and top down approach to analysis of marketing data.
- We don’t just suggest solutions, we have the capability to integrate the best tools for your application so that you keep control over the data.
Here’s some examples scenarios of questions that could be answered with analytics:
- We’ve spent $10m on digital marketing last year in a variety of channels. What should our channel mix be this year?
- Which of our marketing channels are best at acquiring or retaining customers?
- Which customers should we be focusing our acquisition or retention efforts on?
- We have a two sided market place which relies on two key customer types in order to be successful, which geographic locations should we target and in what order to maximise results?
- How can we visualise our customer data in such a way that our sales or senior leadership team can understand and draw insight from it?
- How, who, when and why are our customers consuming our content, engaging with us on social media or using our website?