Good, clean data is the DNA of any analytics-driven marketing strategy and having access to the right data, at the right time and the right place has long been considered marketing nirvana. The struggle, of course, lies in pacing and prioritizing the organic development of comprehensive data management capabilities and balancing them against more tactical campaign/website measurement objectives. This is especially relevant for SMBs who do not necessarily have the IT bandwidth/scale or for that matter, any compelling business needs to build complex data infrastructures in-house.

This is where we like to push the concepts of data-as-a-service using hosted marketing data marts. ‘Outsourcing’ data preparation, integration and hosting provides a powerful, and low-risk approach to incrementally building up your data maturity with explicit validations of ROI assumptions and business impact for both marketing analytics and business intelligence use cases. The underlying rationale is simple. Leverage third-party expertise in marketing measurement technology best practices, ETL, and data modeling while retaining the business analytics and reporting functions in-house. This allows for thoroughly validating Marketing ROI assumptions before committing budgets to roll out organization-wide changes around technology, people, and processes which are critical for building enterprise-grade data infrastructures.

Here are 3 specific considerations to review when making a build vs. buy decision for marketing data infrastructures-

Cost – The cost of building data infrastructures consists of both capital investments (software license fee, hardware provisioning etc.) and on-going maintenance and support charges. In a majority of the scenarios, the cost would probably be the strongest driving factor in deciding between on-premise vs. hosted data approaches. Designing, building, and maintaining large-scale data marts is no mean feat and requires deep technical expertise around platform technology options, ETL techniques, data modeling best practices and systems engineering. Of course, a far more important consideration is around common lack of functional skills and domain understanding of marketing and its component business processes amongst technical consultants. Outsourcing data infrastructure delivery to qualified providers can help a great deal in addressing all these issues quickly and within organizational constraints. Using attractive pricing models (pay as you go, retainers etc.) companies can easily shift focus away from data assembly to more value-added business analysis.

Time to insight delivery – Building up scalable data marts takes time. With typical marketing campaigns running from between 6 to 8 weeks, it is unrealistic to expect meaningful investment returns for a better part of marketing investment cycle if building the data infrastructure capability in-house. New frameworks need to be devised, data profiling and quality assessment standards need to be built, data models and taxonomies need to be defined, and complex ETL jobs need to be written along with robust error handling. Finally, all this needs to be done in a repeatable manner so as to avoid patchy, piecemeal implementations. It is not hard to see how this can leave little time for basic data analysis let alone making in-flight campaign adjustments based on insights. Using hosted data marts, the timelines for building underlying data infrastructures can be condensed significantly allowing a greater proportion of time to be spent on actual analysis.

Need for experimentation – Many Marketers face the need for experimenting with new propositions and products and measure their bottom line impacts on cost, revenue, and process/organizational changes before rolling out changes company-wide. Take the example of analytics models for marketing attribution measurement. Numerous considerations need to be evaluated including the complexity of link tagging, the number of touch points between introduction and conversion, tracking both converters and non-converters, the way media buy contracts are structured and whether they can take advantage of attribution results, governance bottlenecks, capital investment considerations and so on. Testing out the results using small data samples from a hosted data service validates project ROI assumptions without having to make significant upfront technology investments and large-scale organizational changes.


With so much data proliferation happening in marketing, aggregating, cleaning and transforming of data from disparate data sources can often become a far bigger challenge than making business sense of that data and driving bottom-line marketing optimization instead. The data-as-a-service approach outlined above can provide a cost-effective alternative to building organic data assembly capabilities and should be seriously evaluated as a compelling, commercially feasible business intelligence technology strategy.

Article purpose

A short teaser article to articulate why Business intelligence and Analytics delivery Customers should look to outsource data integration work. Explains how this allows them to focus on data analysis tasks as opposed to getting bogged down in architectural plumbing issues around ETL and data integration.

Target audience

Marketing data analysts and customer insights professionals looking for an easy, quick to process supply of reporting and/or analytics-ready data.

About the Client

A leading EU Consultancy into business intelligence consulting for multiple industry verticals.