Data Culture

Data is only as useful as its purpose. Teams that operate with a data culture move away from collecting data for the sake of having data and move into a more insights-driven approach to tapping into what’s available behind those rows and columns of information.

Big data is full of opportunities, but there must be buy-in for teams to tap into these opportunities. Establishing a data culture is crucial for building that buy-in and disseminating insights from the massive amounts of information daily. It’s here that organizations are able to unify teams and improve marketing, sales, support, HR and more.

Data culture isn’t something that can be hired out, though. Without buy-in and complete support from the team, data-centric initiatives will fail to gain traction. However, when paired with the right frameworks, operating a data-centric company culture can lift brands out of the mess of data frustration and onto a path for growth.

A Framework for
Building a Data Culture

Collecting data alone is useless. It’s the insights derived from those data that matter. Leveraging a framework can take the data collected by an organization and use it to make more intelligent predictions and decisions.

The StoryVesting framework is one of the most impactful in building a data culture. This framework ripples through concentric human decision-making and business transformation strategy. Teams that leverage StoryVesting are equipped with a better understanding of creating alignment between internal departments and external factors. It combines insight and empathy by tapping into qualitative and quantitative data to make decisions.

Acquiring the Right Kind of Data to Support a Data Culture

Big data goes well beyond having a wealth of facts and figures. Big data requires the right facts and figures to get what’s needed. These data points come in qualitative and quantitative data, and organizations need both to support a data culture.

Qualitative offers the right, detailed insights into the emotional triggers behind a buyer and employee’s behaviors. Quantitative data is less costly to gather but also lacks a level of depth and understanding around psychological triggers. Pairing both together allows teams that operate in a data culture to extract relevant insights and understand how each department impacts the overall customer experience.

The Building Blocks of Transformation

Acting upon insights is easier said than done. Without having the 3 P’s — people, processes and platforms — in alignment, building a data culture becomes immensely difficult.

Moving from traditional channels and tactic-chasing cultures to more agile data cultures is challenging. However, with the right people in the right places, teams can shift away from micromanagement and move into a more optimized customer experience. It’s through this optimized data culture that new products emerge, experiences improve and overall revenues increase, positioning an organization for long-term, sustainable growth.

The Impact of Data Culture on Brand Experience

Dropped Silo Walls

When all departments have access to the same insights, organizations can build a data culture that trains teams to rely on these collective insights for decision-making. Established silos don’t incentivize teams to lean into data. By removing these barriers, teams can accept data-centric organizational or procedural changes.

Elevated Brand Experiences

Employee experiences often lift as interdepartmental alignment becomes more integrated. Bringing together various departments allows teams to create better products and services to fulfill those target market needs. As a result, the entire brand experience improves from the customers to the internal team.

Cross-Departmental Buy-In

By approaching data as insights that can be leveraged beyond one-off initiatives, teams can create ingrained solutions into the core of the business culture. Information flows more freely between departments allowing for easier decision-making and effective leveraging the data available to your organization.

Operational Efficiency

It’s valuable to revisit processes regularly to ensure there’s data culture infused into the team’s expectations and mode of operation. Monthly, quarterly and annual reviews are all prime opportunities to address how teams leverage data and build a culture around insights.

Customer Experience (CX) Terms

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