Marketing Insights: How to Create an Analytics-Driven Mindset in 5 Steps
It took until the late 90’s before marketers were required to prove how their marketing was performing. The logical conclusion for many businesses was to start measuring that which they were doing.
Unfortunately, this approach has colored the mindset of marketing leaders and has led to organizations starting the process at the wrong end. It may sound simple but we believe the best approach is that marketing leaders should start by finding out the questions that business leaders actually want to know the answers to.
Many companies try to become data driven, but most don’t succeed because they don’t have the adequate skills. Either, because they’re self taught or because they have employed people with a data driven mindset for example data scientists. To actually succeed, companies need to take the next step to become analytics-driven as we take a look at in Step 4: Let the Numbers Lead.
Let’s take a look at a five-step approach you can take to analyse marketing analytics and become an analytics-driven organization.
- Understand Your Business
First and foremost, you need to understand the business by knowing the most important core challenge that your business leaders want answers to. Forming such questions starts with defining the core challenge in a clear way and then defining the insight you need to solve that challenge.
The business challenge you identify might be, “Our marketing doesn’t seem to bring enough value”. Now, think about what Insight you need to solve it. For example “How do I Increase ROI?” Now that you know what kind of Insight you need, consider what factors may impact your Insight.
For example, timeframe, channels, product categories, regions and the data that’s available to you.
Now you can accurately define your business question, for example:
- Which marketing channel drives the most revenue when ?
- Which tactic do I need to improve to optimize ROI in our digital channel?
When considering the metrics, ask yourself, questions like:
- Which KPI’s do I want to evaluate?
- What data cadence do we want to consider?
- Which metrics do I need to get the answer?
Lastly, factor in the data sources available to you with questions like these:
- Which data sources provide the details for the KPI?
- Where do I find this data?
- How can I access it?
- What format is this data available in?
- Is the data cadence daily, weekly or monthly?
- Be Curious
Take a step back and explore the many avenues available to you with the curiosity of an outsider. Once you’ve completed step 1, hypothesize on how to answer the business questions. Ask yourself why you’re doing what you’re doing and which hypothesis you want to test.
When you start with a curious mindset, you’ll be able to come up with new, creative ways of understanding the impact of your marketing efforts, through innovative questions. Once you’ve applied your curious mind to resolve the questions you want to ask. You’ll know what kind of data you need to collect in order to answer your questions in the most effective and impactful way.
- Collect Data
Use data to arm your hypotheses and try out multiple models. For example, if the data available to you is provided in a daily and monthly cadence, dive deep into the impact a day makes versus the impact an overall month can have on your business question. Equipped with the date, can begin to imagine, predict or project what might happen over a 12 month period.
Data analytics helps marketers obtain insights into market trends and shifts, as wells as consumer buying patterns. It facilitates a space for marketing agencies and businesses to develop profitable campaigns based on insights. Take a look at our blog post for insight into .
Analyzing and interpreting data provides a deeper comprehension of the kind of content or messaging that’s most impactful in B2B or B2C cycles. As we’ve touched on, consumer and business data isn’t as valuable as the actual analysis of the information itself. For this reason, the value of collecting data lies in the marketing insights that it can derive and that’s why we emphasised the importance of first establishing your business questions.
- Let the Numbers Lead
Be analytics-driven, not data-driven. Although having the data points is great. The data means nothing if we don’t know how to analyse them which is why once equipped with the data, you should take an analytical approach to your decision making.
Data-driven decision making is the process of making business decisions with an emphasis on a quantitative approach, using number crunching and data processing to yield results as number-based information.
Analytics-driven decision making focused on the “what” and “why”, and can sustain a competitive advantage through understanding how to effectively use and integrate technology, business processes, data and metrics. When striving to be analytics-driven, it’s best to do so in a way that uses analytics technology that has predictive or prescriptive capabilities.
Companies should aim to create a fully-fledged analytics-driven culture throughout their entire organisation that can run parallel to their data-driven vision to be able to actually succeed but many companies are holding back on change management strategies to actually bring such changes into effect. That’s a threshold, that we at Proof would like to change.
And it’s not only us who think this way Emma Storbacka, CEO of Avaus recently shared on her LinkedIn that, “it seems to me that a lot of management teams have started to talk about #data in a completely different way in the last 12 months. Data literacy is being addressed and that is absolutely fantastic. But how about the willingness to change?
- Speak Business
When working closely on a project for months, perhaps dealing on a daily basis with a data scientist there’s a lot of knowledge and industry-specific lingo that you might pick up. You might understand it but that doesn’t mean the whole management team will too.
Once you’ve analysed the data and compiled your hypothesis, make sure that you’re able to translate your findings into a business language that your leaders will find easy to understand. Perhaps that means you should test out your presentation beforehand on a colleague who hasn’t been working on the project with you.
Ask them to stop you when they don’t understand something. Seeing what aspects of your hypothesis are difficult for your colleague to understand will help you to rephrase certain parts so that when you deliver the results to the leaders of your organisation, you’ll be able to deliver maximum impact.
Now that you’re equipped with a five-step approach to analyse marketing analytics and become an analytics-driven marketer, you’re on your way to answering the questions that business leaders actually want to know the answers to but do you have the right tools in place?
Our platform’s ability to automate data management enables you to calculate and visualise future relationships between marketing investments and business performance in real-time.