Invest in data discovery to drive ROI
By Oren Roth-Eisenberg, Director, Strategy
While data may be “king” in the age of personalization, what do you really know about yours? It is hard to fathom just how much data we generate…and how surprisingly little brands actually use. Putting rigor and structure around collecting and analyzing your data from various sources to uncover hidden patterns and trends—a process we call Data Discovery—will help your brand take stock of its current data infrastructure and build a forward-looking roadmap for tailored customer experiences.
Thinking about your data
Not all data is created equal and how data is organized can be a major factor in its use. According to IBM, companies analyze less than 1% of their available data and fewer than 1 in 4 have an enterprise-wide data strategy. IBM also estimates that as much as 80% of data available to brands may be unstructured, making it difficult and costly to use. Tailored experiences within the brand ecosystem can be heavily influenced by the data type, quality, and connectivity within the larger enterprise infrastructure. A simple way to start breaking down your data is:
Data discovery for personalization
Like at the outset of any other major program, performing a structured “Discovery” stage helps create shared understanding between client and agency stakeholders, leading to smoother personalization workstream planning, execution, and optimization.
Robust Data Discovery helps your team audit various types of data available to the brand, while also mapping the structures governing data flow within the ecosystem. Together, these factors will help you:
- Understand current data capabilities and constraints
- Prioritize the channels to pursue in your personalization roadmap
- Identify current and future data strategy needs to build towards
Just starting out on your journey with personalization? Learn more about how to get started by building your strategic foundation, the Brand Blueprint.
We recommend designing your brand’s Data Discovery around three areas:
1. What data you have
The first big step is to evaluate the range of data sources you have to work with. Taking an inventory of your available data can help you prioritize, assign values, and identify information gaps. Consider a set of questions designed to evaluate your data through several different lenses.
- Variety: Do you have a wide pool of data sources to form user segments? Is this the right data to meet your strategic objectives or drive a desired behavior change? Is the data aligned to the customer journey?
- Quality: Do you trust the accuracy of your data how is it verified, or can the data be enhanced by additional contextual data? Is the data usable in its current form, or must it first be structured and scrubbed to glean value? How can other sources or user feedback improve your insight engine?
- Recency: When was the data first collected and are you confident it still reflects user needs? Are these sources static or periodically refreshed—and how will updates feed into your personalization engine?
View data in context of your customer relationship. Depending on channel, the strength, involvement, and trust of your relationship to the target may inform where you begin to personalize the customer experience.
2. How the data connects to feed the larger ecosystem
Personalization requires a flow of data to the right channel; however, it does not always flow smoothly. Consider how open or closed data silos may impact the ability to deliver data to certain channels for tailored experiences.
- Availability: Where in the ecosystem is data held and what firewalls or barriers could prevent using the data in a desired channel? Is the data owned, leased, licensed?
- Gatekeepers: Which enterprise and external stakeholders own (or manage) the data that you must engage as partners throughout the development process?
- Velocity: How quickly can data be shared to trigger deployment of a tailored experience? When data is refreshed, how long will the data take to be actionable within the ecosystem?
Complexity is determined as an analysis of cost and time. Understanding these factors intimately helps plan for the appropriate investment of resources.
3. Evaluate the potential to optimize
Data isn’t static, it has a “shelf life.” Designing a personalization engine that can evolve beyond a fixed point in time must take into account the currency of data, and the speed with which feedback can be incorporated as new information is gained. Can technologies like artificial intelligence (AI) help your brand “learn” to drive real-time optimizations? Does your marketing technology infrastructure support such functionality?
Evoke’s CX offering can help your brand design intelligent systems to fuel personalization initiatives that enhance customer experiences. Let’s talk about how we can power your brand growth.
Data decisions driven by ROI
It’s time we start thinking about data and personalization investment differently. Like purchasing a home, an investment in data can be amortized over multiple tactics and even brands. Upfront and multi-year investments can have significant downstream payoffs in tactical marketing efficiency. Rigorous Data Discovery will help bring to the surface unforeseen contingencies to help determine where personalization may have the greatest ROI. The right strategic partner can help you make sense of the data, understand current limitations, and build the right roadmap for your brand.
The Evoke Center of Excellence on Personalization helps marketers approach the promises of marketing technology with clear, actionable, and human-centered solutions to tailored customer engagement. For more information, email us at email@example.com.