Discussions about improving marketing effectiveness can often focus on the different measurement approaches and advanced analytics tools that marketers should employ.
While these are crucial, it is equally important to consider the goals you are targeting, the data you require to reach them, and the behaviors that will ensure quality data continually informs your investment decisions.
This can be hard, however, when data is a byword for complexity and marketers are under pressure to demonstrate effectiveness now as well as over the long term. To help you and your team overcome these challenges, here are six things we recommend:
1. Know your goals
Before you dive into data, take a step back. Now more than ever, marketing needs to drive growth and demonstrate its value to the wider business. One way you can do this is by ensuring your goals align with your company’s strategic objectives and KPIs.
One retailer we work with framed a campaign that focused on changing price perception in the short term around the company’s growth driver of providing inspiring, healthy, and affordable food. If your goals are more aspirational, it is particularly important to ensure they are linked to more concrete metrics.
By tying goals back to metrics such as brand perception, price per unit sold and sales volume, you get clarity about what you want to achieve and how you can grow the bottom line, and ensure your work resonates with the C-suite. Crucially, it also confirms what data you need to collect and measure.
2. Find the gaps
Having a clear understanding of the data you have and the data you need to reach your goal is the next important step. Performing a gap analysis with a MECE (mutually exclusive and collectively exhaustive) framework is an approach that can help to work this out. If your goal is to increase sales, for example, do you have granular, near-time data about how customers respond to your marketing campaigns?
Data about how specific audience groups in different geographies behave depending on the channel, creative, partner, or weather can significantly boost effectiveness by enabling you to make tactical decisions at speed. But it’s important to recognize that not all gaps can be filled overnight. Thinking in terms of the best available data, which meets your immediate needs, and the best possible data, which builds best-in-class assets over the longer term, is a pragmatic way to improve the quality of your data.
3. Augment and enrich
Knowing how to augment and enrich existing data sources can improve visibility, speed-to-insight, and decision-making. Marketers can do this is by considering what data sources are available beyond those related to brand and media. For example, diverse audience data can reduce bias in your analyses, supply chain data can help to ensure products are where they are needed with marketing investment to support them, while demand signals can provide more accurate sales forecasts.
It’s important to remain focused on the end goal so that you avoid overinvesting and end up with a lake of redundant data assets; you’re unlikely to need 50 different metrics to help forecast how consumer spending patterns may change, for example.
4. Be privacy-first
While government regulation and privacy restrictions have created data privacy challenges for marketers, you can still thrive in this fast-changing environment. Being committed to a privacy-first approach is a good starting point, as it makes you balance the trust you want to build with your customers with the security and transparency needs of your organization. While it’s important for brands to know their customers in a privacy-first way, it’s equally important that consumers can feel it too.
5. Ensure equitable access
With a foundation of quality, privacy-first data in place, it is essential that all relevant stakeholders can access it. Data silos remain a challenge in many companies and removing them is key to delivering insights that drive growth. Technology, such as machine learning, automated data ingestion, analytics tools that sit behind firewalls, or dashboards that provide a business-wide view of data, can help to do this.
However, if it is also stuck in a silo then its potential will be severely restricted. To ensure technology adds value, more people need to have equitable access to more data. It’s crucial that all stakeholders can make “apples to apples” comparisons.
6. Prioritize change management
Even if you have enacted the preceding five recommendations, effectiveness over the long term will be difficult unless data-driven behaviors become embedded in your organization. We know from experience that many companies don’t focus enough on change management.
It can be a hard journey to undertake, but it is essential for success. Key ingredients include clear communication, training and support for employees who are not data specialists, controls where necessary, and ongoing analysis.
Contact Russell to learn more about how you can become more data-driven.
This article was originally published on the ANA’s website. Click here to view.