Turning customer data insights into marketing strategy

How do you turn customer data into those powerful lightbulb insights that drive marketing decisions? Even with powerful tools for aggregating, consolidating, and visualizing data, it’s not easy. 

Despite all the help we get, there’s room for human interpretation to create insights and roll them into our strategy. And where there’s room for human interpretation, there’s room for error.

Data is raw, unprocessed facts. Insights are the meaningful conclusions we draw from that data. Therein lies the challenge: we need quality, real-time data cleaned, normalized, and accurate. 

These days, data collectors grapple with privacy concerns, cookie deprecation, and poor quality data from disparate sources. To future-proof our targeting strategies and ensure they’re still personalized, we’ll need to access and activate zero- and first-party data effectively. We’ll also need to store our data in a way that mitigates human error or inconsistency from multiple sources.

Using the right tools for data storage and activation will get you to the insights stage faster. That’s why we have this framework for using Snowflake and a CDP (in this case, Simon Data) to get you to the strategy stage quickly.

The marketing data and insights disconnect

We’ve highlighted the challenge: Data and insights are not synonymous. Between the two is often a disconnect that’s the fault of changing regulations, data siloes, and manual workflows.

The shift from 3PC

Now that privacy regulations tighten on third-party data, marketers will need to be more economical with the information they have access to. The GDPR and CCPA regulations, in addition to the deprecation of third-party cookies (and cookies becoming opt-in only on Chrome), are really a good thing: they protect consumer privacy, which builds trust. 

In the future, marketers will depend more on zero- and first-party data. CDPs like Simon enable the seamless organization, access, and activation of zero- and first-party data, ensuring compliance with privacy regulations while still providing valuable customer insights.

Data silos and manual workflows between marketing teams

When every tool is clamoring to be insightful, it creates a lot of noise. One of your tools might provide accurate data on email deliverability, another on open rate, and another tool could track replies. How do you reconcile this data?

This is why many organizations struggle with disjointed data silos. Finding the most accurate picture of your email marketing strategy requires consolidating all this data from multiple sources into one place.

A manual workflow to consolidate data hinders your ability to quickly extract insights. Without quick insights, you can’t accurately segment your audience, personalize marketing, or change course with informed, data-driven decisions. Instead, your marketing strategy will be reactive.

Building a foundation for strong marketing data insights

So, how do we turn this boat around? Let’s begin with the end in mind, then work our way from there to the right data collection strategies.

Define your marketing goals

Good data insights start with clearly defined goals. Your goals drive the data insights you unearth. 

It’s like the scientific method: you start with a hypothesis so you can control variables and run a repeatable test. If your goal is a higher MQL rate, your hypothesis might be that on-page conversion efforts are falling flat. This gives you something to look for.

Unlike a scientific test, however, your data audits might run on multiple hypotheses at once. You might look at on-page conversion efforts, but you might also have a hypothesis that your ICP is unlikely to MQL.

Now that you have marketing goals (and therefore goals for your data analysis), how do you get to the bottom of these questions? Find the data sources and platforms relevant for your goals.

Quantitative data sources are typically straightforward — both to analyze and aggregate. Most  quality responses can be compiled in spreadsheets, in your martech tools, or with your CDP.

If you’re looking for qualitative insights, seek platforms to gather survey data, reviews, social media interactions, email correspondence, and so on. This is trickier to do, and it’s where manual workflows break down.

For this reason, it’s here that a data cloud platform and CDP will come in handy. These tools can save hours of manual work and reduce human error with a single source of truth. Snowflake would help you scalably store and process a large dataset, while a CDP like Simon helps unify and activate data.

Translate insights into the ultimate marketing strategy

Now, you have the data wrangled and readable. The insights you extract will depend on the goals you’ve established. At this step, you translate your findings into actionable marketing strategies.

Ideally, your insights can closely tie to KPIs or revenue — that’s the dream of every marketer. Tracking metrics like purchase history, customer segment behavior, campaign effectiveness, repeat purchases, and customer loyalty and retention metrics are all indicators that tie into revenue-creating activities. 

If we follow the scientific method, these insights lead to implications for further study — ergo, your strategies. Marketing is all a process of iterable testing, and your next strategies will be tests informed by previous experiments.

For example, if the data reveals a high rate of repeat purchases from a particular customer segment, you should develop personalized campaigns to further engage this group. Similarly, insights into campaign effectiveness can guide the optimization of future marketing efforts once you collect data on your success.

But this is where the directions get murky, isn’t it? That’s because there’s no one-size-fits-all step for this part. A marketing team has infinite ways to use data to inform strategy. Let’s get into an example of insight-to-strategy that helps this section feel more concrete.

Example: Personalized email campaigns

You manage email campaigns for a popular fashion retailer. Lately, you've been facing a perfect storm of declining engagement metrics: clicks, CTRs, open rates, and even subscriber count are plummeting. This isn't good news for your boss, and it's certainly not ideal for your career. You need a data-driven explanation and a solid plan to turn things around.

Luckily, you have a wealth of real-time customer data stored in Snowflake. By feeding this data into a CDP like Simon, you can unlock valuable insights.

With Simon's segmentation and audience analysis capabilities, you uncover distinct shopping behaviors among different customer groups. For instance, you've been bombarding everyone with emails about new arrivals, restock alerts, sales, and promotions. While this shotgun approach might have worked initially, it's now overwhelming customers and drowning out your message.

Your analysis reveals that new customers are more likely to unsubscribe after receiving new arrival emails, while loyal shoppers are ignoring beginner styling tips. It's clear that a one-size-fits-all email strategy is no longer effective. The solution? Segment your audience and tailor your email campaigns to each specific group.

In a perfect world, you dive into segmenting your audience with the help of your trusty CDP. Armed with customer data, you create highly specific segments. For instance, you identify a group of frequent shoppers who primarily purchase accessories. This segment becomes your "Accessory Addict" group. Another segment, "Weekend Warriors," consists of customers who make large purchases on Fridays and Saturdays.

With these segments defined, you craft tailored email campaigns. The "Accessory Addict" group receives emails highlighting new accessory collections, limited-edition pieces, and styling tips. The "Weekend Warriors" get emails with exclusive weekend deals, outfit inspiration, and personalized product recommendations based on their purchase history.

This level of personalization is a game-changer. Open rates soar, click-through rates skyrocket, and customer satisfaction improves. Your boss is thrilled with the results, and you've successfully transformed your email marketing strategy. 

While it's unlikely that you'll never need to experiment again, this data-driven approach has laid a strong foundation for future success — and at least your data is clean and actionable.

Building a data-driven culture

Now that your first adventure in data insights is over, the next step is baking data-backed decisions into company culture. Unsurprisingly, the key to breaking down silos and freely sharing data lies in communication between teams.

The best marketing insights come from frequent collaboration between data teams and marketers. Consider regular syncs and KPIs that depend on collaboration, encouraging you to work together. You can use your meetings to plan joint projects and sync on reporting.

Collaboration will also encourage you to break down data silos that impede the flow of information. Because you’ve likely integrated data from all your platforms into a single source of truth by this point in order to unearth the best insights, why stop? Make this standard procedure. If you have to commit to  a manual workflow to consolidate data, do this process regularly.

Lastly, keep learning and iterating. That’s how you avoid being stuck with tech debt and decades-old data software. Be sure to learn from other marketers regarding their hypotheses, the data models they use, and the insights they unearth.

Conclusion

With that, you have the lather-rinse-repeat of turning customer data insights into marketing strategies. It isn’t easy, and that’s why many marketers won’t do it. Fortunately, modern software makes it simpler than ever. 

If you haven’t given a CDP like Simon a chance, now’s a good time to start. Simon makes activating data nearly subconscious, requiring the ever-busy marketing team more time to focus on other aspects of the job. Learn more about how Snowflake and Simon work together to help marketers deliver the experience customers crave.