Marketers today are drowning in data, but just having access to it doesn’t automatically lead to smarter decisions. The real challenge is turning all that information into meaningful insights that actually move the needle on customer engagement and campaign performance.
Many marketing teams hit roadblocks with data systems that are too complex to navigate without engineering help. This slows execution, limits experimentation, and disconnects marketers from their audience. In fact, 54% of companies say their biggest challenge to data-driven marketing success is the lack of data quality and completeness.
Blueshift’s Data Studio bridges this gap with powerful, self-serve tools that let marketers enrich, explore, and activate customer data without writing a single line of code. With added capabilities like Computed Attributes and RFM Scores, Data Studio adds a critical layer of intelligence to how marketers segment, personalize, and trigger campaigns based on real-time customer behavior.
In this blog, we cover three common challenges that marketers face when activating customer data, along with actionable strategies to break through them.
How Can Marketers Clean Up and Organize Messy Customer Data?
As data flows in from multiple channels, platforms often accumulate hundreds of profile attributes, from standard fields to one-off custom dimensions. The result? A noisy, cluttered environment where it’s hard to tell which attributes are relevant, reliable, or even being used.
This lack of visibility leads to:
- Confusion when building segments and journeys
- Mistakes in personalization
- Delays caused by needing analyst or developer support
Blueshift’s Data Studio cuts through the noise by showing how each attribute is being used across segments, campaigns, and templates, giving marketers instant clarity on what matters. With sample values, data types, and in-line descriptions, teams can confidently interpret and clean up their data, reducing clutter and focusing on high-impact attributes.
By eliminating guesswork and surfacing the most actionable insights, Data Studio empowers marketers to work faster, personalize smarter, and ultimately boost operational efficiency and deepen customer engagement.
How Can RFM Scoring Help Marketers Engage Loyal and At-Risk Customers?
Marketers often need to identify which customers are loyal, slipping away, or at risk of churning. Whether it’s crafting retention offers or recognizing brand advocates, it all starts with a clear, data-driven way to understand customer value.
Without a standardized framework, teams often struggle with:
- Manual analysis and static lists
- Custom scoring logic that’s hard to maintain
- Delays in launching campaigns due to unclear targeting criteria
Blueshift makes this process seamless with built-in RFM scoring.
What is RFM Scoring?
RFM stands for Recency, Frequency, and Monetary value, a model used to segment customers by how recently they purchased, how often, and how much they spent.
This is a proven marketing framework used across retail, ecommerce, travel, and financial services to prioritize and personalize engagement. Blueshift automatically calculates these scores using the data already flowing through the platform, no spreadsheets or engineering support required.
Marketers can use these scores to:
- Build smarter segments (e.g., high-value but at-risk customers)
- Tailor messaging (e.g., urgency cues for dormant users)
- Measure performance across different value tiers
All of this happens directly within the workflows where targeting and personalization occur. With a clear, automated view of customer value, Blueshift enables marketers to prioritize smarter and engage with precision.
How Can Marketers Target High-Value Purchases Across Specific Channels?
Let’s say a retail marketer wants to build a campaign targeting customers who made high-value purchases from the footwear category via offline stores in the last 30 days. The goal might be to reward loyal in-store shoppers or promote early access to a new collection.
To do this, the marketer needs to combine and aggregate event-level data across:
- Purchase categories
- Sales channels (online vs. offline)
- Transaction value over a specific time frame
Standard segmentation alone can’t handle this complexity. It requires conditional logic and roll-ups at the profile level. Moreover, even if the segmentation problem is solved, using that data in message personalization often demands complex computations. As a result, marketers often rely on data teams to write custom queries or pull lists from the warehouse, slowing time-to-launch and adding friction to campaign execution.
Blueshift solves this with Computed Attributes. With these, marketers can easily define custom fields like “30-day offline footwear spend” or “number of in-store purchases this month” using flexible configuration options. These attributes update automatically and are immediately usable in segments, journey triggers, personalization templates, and reporting, keeping campaigns timely and highly targeted.
By making complex aggregations self-serve, Blueshift gives marketers the agility to act on nuanced customer behavior in real time without waiting on data teams or compromising on precision.
How Does Blueshift’s Data Studio Turn Raw Data Into Actionable Insights?
With the Data Studio and its advanced capabilities, Blueshift empowers marketers to go deeper into their data without leaving the platform or waiting on external teams. Computed Attributes help define metrics tailored to your business. RFM Scores provide a reliable lens on customer value. And the Data Studio adds the visibility needed to confidently navigate and use your data effectively.
By turning raw data into structured, actionable signals, marketers can:
- Move faster
- Personalize more effectively
- Build journeys that mirror real customer behavior
…fueling both efficiency and engagement.
Ready to activate your data like never before? Book a personalized demo to see Blueshift’s Data Studio in action and unlock smarter marketing today.
