Marketers have long relied on data to inform decisions.
But the way we use data is evolving.
In the past, isolated events were enough justification for making marketing decisions.
Today, increased competition and shrinking budgets mean marketers need an integrated, intelligent activity overview to make growth-enabling decisions and deliver better customer experiences.
That sounds like a lot of buzzwords.
Let’s break down the role of data analytics in marketing to demonstrate how an integrated, proactive approach is replacing reactive decision-making.
The prevalence of micro-moments and omnichannel customer experiences means data comes from everywhere.
Every customer interaction, click-through, impression, bounce or browsing session provides several levels of customer data that could be useful.
But there’s also a lot of noise.
Marketers must start with a clear use case to decide what data is valuable.
What data does your organisation possess to segment customers, and what’s missing?
The answer depends on your customer segmentation strategy.
In the case of B2B organisations like business insurers, the customer’s industry, job function or membership status might be more relevant.
Better experiences often result in more customer loyalty and increased revenue.
Data analytics plays a pivotal role in understanding – and improving – the customer experience.
After segmenting customers along the relevant lines, data opens the door to understanding how individuals within those broad groups view the organisation.
We’ll elaborate on that shortly.
Digital marketing today is not a one-way communication system.
It is an agile process of continuous improvement based on data analytics.
Using the customer segmentation and customer experience strategies, both of which should support business goals, the role of data analytics is to assess performance and inform the next steps.
If the role of data analytics in marketing is to:
…then how do these ideas come together in a modern marketing team?
In other words, how do marketers use information and analytics tools effectively without drowning in data?
The death of third-party cookies, expected in 2023, signals an opportunity to reinvent the role of data analytics in marketing.
Zero-party data (willingly and proactively shared with the brand) and first-party data (information obtained directly from customers or audiences) are significantly more informative than third-party data (anonymised, packaged and sold by another organisation).
Although zero- and first-party data are harder to collect, they provide much deeper insight into audience intentions, preferences and behaviours.
Adjusting your marketing strategy to offer value in exchange for capturing direct data will result in richer customer profiles.
According to Google and Econsultancy, 86% of senior executives agree that eliminating organisational siloes is critical to improving data analytics capabilities.
These powerful platforms enable sharper segmentation, better customer experiences and more informed, customer-focused decision-making.
With the proper instruction, machines can optimise targeting and delivery, freeing up marketers’ time to focus on strategy.
As the role of data analytics in marketing becomes more integral, equipping teams with the tools to manage an influx of data is mission-critical.
Trust technology to gather, combine and analyse data.
The marketer’s role is to interpret the customer experience and make recommendations.
However, data analytics tools can automate many tasks:
Data security and trust remain issues, even as data collection policies change worldwide.
According to Pew Research, 79% of Americans are concerned about how companies use their data. Most (81%) believe they have little to no control over the data companies collect, and 62% think it’s impossible to go through a day without having personal data collected.
How many customers will limit the data they provide when the choice is put squarely in their hands?
Marketers need to be on the front foot, collaborating with IT and software partners around data privacy, and making their data handling policies transparent to maintain customers’ trust.
Biases can – and often do – find their way into AI algorithms, just like they have appeared in human decision-making since forever.
One way to tackle bias is to augment first-party data with behavioural data.
Behavioural data is based on experience, not assumptions. Of course, it’s tricky to track (and act on) every interaction, which is why marketers typically rely on third-party data to segment customers into high-level personas.
But if our goal is to provide the best customer experience, third-party data alone simply doesn’t cut it.
Features like Attribution IQ, the intelligence behind Adobe Analytics and Customer Journey Analytics, help marketers analyse customer behaviour in non-linear and cross-channel journeys.
Using first, second and third-party data together with interaction data, Attribution IQ enables marketers to focus on behaviour and analyse marketing effectiveness without relying on demographic data.
Data analytics’ role in marketing has changed significantly in the last 10 years.
But it’s about to change again.
The tools and techniques that rose to prominence in the last decade are improving to give marketers and customers more control.
Digital transformation, as we discussed in an earlier blog, is now about deploying integrated technologies to improve the customer experience.
There are three key steps to preparing for the change in marketing and data analytics.
Start with customer segmentation and customer experience strategies that accurately reflect your audience.
This could mean investing time and energy into zero- and first-party data collection before your marketing can evolve.
That’s perfectly fine, as long as the strategy supports business growth.
Turning data into decisions is only possible with the right martech stack.
Once you set your sights on a customer experience strategy, kit out your arsenal with the data analytics tools that will enable the step up.
The final puzzle piece is upskilling your team to use data for business growth.
The line between training for a new tool (e.g. Adobe Target training) and a new process (e.g. personalised offers) is often blurry, which is why strategy comes first and the rest follow. In other words, clarify what you’re trying to do then decide on the best way to do it.
Strategy, people and process work together in successful marketing teams to deliver exceptional customer experiences and insightful growth decisions.
TAP CXM are a collective of leading customer experience consultants and Adobe Marketing Cloud specialists. Contact our team for personalised advice on evolving your data analytics capabilities beyond 2022.