# Marketing analysis, reporting and data products | Measurelab > Marketing reporting and analysis in Data Studio (formerly Looker Studio), plus data products such as forecasts and models, built on data you can check. Source: https://www.measurelab.co.uk/solutions/data-products/ ## Marketing analytics & data products Bring us the change you can't explain or the customer question you can't answer. We investigate it, then build what helps: a report people use, a forecast or model, or a tool your team relies on day to day. ## From question to action Start with the question and work towards something your team can use, check and maintain. ### Start with the question The change you can't explain, the systems that disagree or the customer question your reports can't answer. - Performance changes - Numbers that disagree - Customer questions [Deciding what matters first? Framing](https://www.measurelab.co.uk/how-we-work/#start) ### Connect what happened next Join acquisition to what came after, so a lead or customer is judged by the business it became. - Leads to customers - Customer value - Joined acquisition data [Intelligence platforms](https://www.measurelab.co.uk/solutions/intelligence-platforms/) ### Build the answer An investigation, a report people use or a model, tested with the people who rely on it. You can also ask questions of an agreed dataset in plain English. - Analysis - Marketing reporting in Data Studio - Forecasts and segments - Plain-English questions [Making an AI agent accurate in BigQuery](https://www.measurelab.co.uk/insights/blog/how-to-make-an-ai-agent-accurate-in-bigquery/) ### Use the results Results in your customer and marketing tools, with agreed permissions and a way to review what happened. - Audiences and segments - Results in your marketing tools - A record of what changed [Audience activation in five steps](https://www.measurelab.co.uk/insights/blog/audience-activation-in-5-simple-steps/) ## Tools we work with Most of this work runs on BigQuery, with reports in Data Studio. These are the other tools we often work with. Reporting and analysis reporting-and-analysis ## What changes for you Questions about performance get answered with evidence your team can follow. Leads and campaigns are judged by the customers and revenue they turned into. The reports and models we build are tested with the people who use them and documented so your team can maintain them. When you decide what to change, the reasoning is in front of you. Guides and conversations from our team on reporting, measurement and modelling. ### [Building dashboards like a pro](https://www.measurelab.co.uk/insights/podcast/building-dashboards-pro/) ### [Who you Lookering at?](https://www.measurelab.co.uk/insights/podcast/who-you-lookering-at-with-jj-reynolds-lookerstudio-vip/) ### [MMM, MTA and the future of marketing measurement](https://www.measurelab.co.uk/insights/podcast/future-of-marketing-measurement-janos-moldvay-funnel/) ### [Marketing incrementality, attribution and ROI optimisation](https://www.measurelab.co.uk/insights/podcast/marketing-incrementality-attribution-roi-optimisation-coppel/) ### [Forecasting analytics with machine learning](https://www.measurelab.co.uk/insights/podcast/forecasting-analytics-machine-learning-richard-fergie/) ### [GA4, the CDP you didn't know you had](https://www.measurelab.co.uk/insights/podcast/ga4-cdp-of-the-future-rickdronkers/) [Everything we've published on data analysis](https://www.measurelab.co.uk/insights/tag/data-analysis/) The work, in practice ## [Finding out why people phone](https://www.measurelab.co.uk/insights/success-stories/call-propensity-analysis-for-sanderson/) Sanderson could not see what happened before a customer picked up the phone. We joined GA4 to their ordering system and call-centre data in BigQuery, keyed on user ID, which showed which pages people were on immediately before they called, and so which ones to improve first. Sanderson Design Group Web, ordering and call-centre data joined up ## [Campaign reporting people can use](https://www.measurelab.co.uk/insights/success-stories/howard-kennedy-ga4-data-content-performance-reporting/) We agreed useful measures with stakeholders and built an automated campaign dashboard, so colleagues could access the figures themselves. Howard Kennedy Less manual reporting ## [Following campaigns through to enrolment](https://www.measurelab.co.uk/insights/success-stories/unifying-student-data-for-university-of-exeter/) Marketing interactions, applications and enrolments connected in a reporting dataset, helping the recruitment team understand the student journey. University of Exeter Cost per enrolment in view ## Product launch forecasting We built a custom forecasting engine in BigQuery using historical data to predict launch performance for the Google Store. EMEA and APAC teams use it to optimise stock levels and identify cross-sell opportunities. Google Store EMEA and APAC optimisation ## Subscription funnel optimisation BFI's subscription products were losing customers at particular lifecycle stages without it being clear where. We analysed the full funnel in BigQuery, from acquisition through engagement to renewal, so the friction points driving churn could be seen and prioritised. BFI Friction points in the renewal journey identified ## [Anomaly detection with BigQuery ML](https://www.measurelab.co.uk/insights/blog/what-we-learned-building-ai-agents-for-clients-and-ourselves/) We deployed ARIMA models in BigQuery ML that check EDF's data patterns every hour and post an alert to Slack when they break, so problems surface before someone spots them in a report. EDF Energy Hourly checks with Slack alerts ## Data democratisation Monzo's data team could not keep up with every reporting request from a fast-growing company. We delivered Data Studio training and self-serve enablement, giving non-technical teams the confidence to interrogate data without compromising governance. Monzo Self-serve analytics at scale ## What clients say ## Tell us what you need to know Tell us about the report, question or repetitive job getting in your way. A single question can be a piece of work on its own, using the data you already have where it is good enough; it does not have to start with a new platform. We don't buy or sell media or take a cut of ad spend, so the analysis isn't tied to a channel we're selling. Discuss your analysis