Analytics/Business Intelligence

Customer Insights & Feedback: The qualitative "why" behind the quantitative "what." When Analytics reports that 20% of customers drop off at a certain webpage, CX can provide the context from customer feedback (e.g., "The 'next' button is broken on mobile," or "The shipping costs are a surprise").

Journey Mapping Contributions: Customer journey maps that help the Analytics team understand the key moments and touchpoints to measure. This ensures they are tracking data that is truly indicative of the customer's experience.

Advocacy for Customer Needs: Championing the need to invest in capturing and integrating experience data (e.g., survey responses, support contact reasons) with operational and behavioural data to create a holistic view of the customer.

Process Improvement Suggestions: Providing clear, well-defined analysis requests with specific hypotheses. For example, instead of asking "Can we get data on churn?", ask "We hypothesise that customers who experience a delivery delay are more likely to churn within 90 days. Can you help us validate this?"

Data & Analytics: Feedback on the reports and dashboards they produce. CX can advise on which visualisations are most insightful and which metrics are vanity vs. actionable, helping the Analytics team refine their output for maximum impact.

Regular Communication Channels: Establish a recurring "CX Analytics Huddle" to review key dashboards, discuss emerging trends, and prioritise the backlog of analysis requests.

Joint Initiatives & Projects: Partner on creating a definitive "CX Health Dashboard" that blends key operational data (e.g., usage, transactions) with experience data (e.g., CSAT, CES, NPS). Collaborate on deep-dive analyses like customer segmentation, where CX provides the qualitative personas to enrich the quantitative clusters.

Data Sharing & Reporting: Systematically structure and quantify qualitative data (e.g., by tagging support tickets and survey comments by theme) and share it with Analytics. This enables powerful mixed-method analysis, combining the 'what' and the 'why'.

Cross-Functional Training/Workshops: Invite analysts to listen to customer calls or watch session recordings to bring the data points to life. In turn, ask the Analytics team for training on self-service BI tools (e.g., Tableau, Power BI) to empower the CX team to answer their own foundational data questions.

Attending Their Meetings: Request to join their sprint planning or prioritisation meetings to advocate for the importance of CX-related analyses and to understand their capacity and competing projects.

Active Listening & Empathy: Recognise that the Analytics team serves the entire business and has a long list of priorities. Approach them as a collaborative partner in discovery. Help them understand the business value of a request to aid in prioritisation.

"What is the most critical question about our customer's experience that we currently cannot answer with data?"

"How can we move beyond simply requesting reports and instead partner with Analytics to uncover deep, actionable insights?"

"How can we structure our qualitative feedback to make it easy for the Analytics team to integrate it into their models and dashboards?"