If you were to travel back in time, say to 2010, and enter a discussion on marketing strategy, you’d notice a distinct change. Back then, the focus was on the ‘Big Idea,’ that one creative concept to connect instantly with your target audience. Fast forward to today, and ‘Big Data’ has taken center stage in most modern marketing conversations. While data has always played a role in shaping marketing strategy, it now sits at the forefront, especially data at the individual customer level.

So, why has data become the driving force of marketing?

The answer lies in meeting the ever-increasing expectations of today’s customers. Research reveals that customers form rapid judgments about brands based on their experiences across all touchpoints. To deliver personalized experiences that align with these expectations, companies need data.

However, navigating this data transformation hasn’t been straightforward for many brands, whether they’re startups or well-established giants. This challenge isn’t solely about staffing; it’s a hurdle faced by organizations of all sizes.

That’s where the crawl->walk->run framework comes in, helping marketers tackle the digital data transformation step by step.

STEP ONE -> Take Inventory of Your Data
The sheer volume and diversity of data available to organizations today are unprecedented. The first step for many marketers is understanding the data they have access to and what it signifies. Ask yourself questions like:

– Do we have audience data related to our latest email campaign?
– Can we measure the performance of that campaign’s audience?
– Is there recent purchase data for this audience?
– Do we have web analytics data on their site visits?

For many marketers, the answer to these questions might be a hesitant “maybe.” Collaborating with cross-functional teams to identify where your data resides, how it’s collected, and by which teams is essential.

The digital landscape has inundated organizations with data. Conducting a thorough inventory of your data assets is one of the most valuable things your brand can do.

STEP TWO -> Unify Your Data
Once you’ve taken stock of your data, the next challenge is unifying it. This involves understanding complex customer journeys, such as:

– A customer opening your email, browsing your website, and adding items to their shopping cart.
– The same customer potentially abandoning their cart.
– Later, after viewing a digital ad from your ‘cart abandonment’ retargeting campaign, they return to complete the purchase.

This may seem straightforward, but unifying the data involved in managing such journeys is no small feat. Technical hurdles can arise when integrating systems that may or may not be ready to cooperate. Questions like:

– Are we working towards resolving customer identity across systems where data resides?
– Is our marketing technology optimized for individual channel performance, or does it use data across systems to optimize the entire customer experience?
– Are comprehensive data sets driving the customer experience at every engagement point, even outside marketing touchpoints?

Aligning teams around a data unification strategy can be another challenge. This often means adopting a more customer-focused approach that deprioritizes traditional channel-focused marketing strategies, which treat customers differently across touchpoints. Gather your team and devise a plan that everyone can support, one that helps transition from channel-focused to customer-focused strategies.

STEP THREE -> Engage and Optimize
The final piece of the puzzle involves using your data assets to enhance the customer experience. The goal for most marketing organizations is to understand what experiences customers seek and then make the path to those experiences as smooth, personalized, and frictionless as possible. Unified data will drive this effort, ensuring each customer interaction aligns with their expectations. For instance, if a customer has an open service ticket, it’s probably not the right time to engage them with a marketing message. By integrating service and marketing data, you can prevent such mismatches.

This process is ongoing and never truly finished. Your data should not only drive engagement but also provide valuable insights into your target customers. It’s an opportunity to use data analysis and AI to continually optimize your marketing outcomes. For example, you might discover that a significant portion of your best customers are avid adventure travelers. This insight can shape not only marketing strategy but also product and business strategy. It could lead to testing travel-oriented campaigns or partnering with a travel brand.

We live in a constantly changing and disruptive era. The shifting business landscape can easily overwhelm marketing professionals and organizations. That’s why it’s crucial to assess your digital and data transformation goals, understand where you currently stand in your journey and start from there. To reach your destination, you must first know your starting point.