The marketing technology 'ecosystem' has become a quagmire

Marketing & business data is siloed and difficult to integrate. Insights which could lead to revenue increases & cost reductions are lost. CMOs are still struggling to get automated, timely insights on their marketing performance.

Copy-pasting Google Analytics data into Excel is not the answer

Not real revenue

Google Analytics is a proxy for real revenue, but it is never fully accurate due to refunds, and missed or duplicated transactions caused by configuration errors or Javascript blockers.

No customer view

Google Analytics uses cookies to try and recognise new site visitors and returning visitors, but it does not have an accurate view of new vs. returning customers. Thus you can not measure campaign performance through the lens of customer acquisition.

Error prone

Manual work like this is prone to error. This raises the risk of key business decisions being made based on incorrect data.

Time-consuming

Repetitive and time-consuming task which starts from zero with every new piece of analysis.

Waste of resources

80% of analyst time is spent cleaning data. This time could be better-utilized for strategic thinking & complex modelling.

Snapshot in time

Static analysis data does not unlock rich insights, such as channel-level LTV, new vs. existing customer analysis and more.

Off-the-shelf data integration tools won't solve the problem either

Unstructured data

Off-the-shelf tools can pull data from multiple platforms, but they do not offer help with the most difficult part: structuring and joining the data to make it usable.

Quantity not quality

Off-the-shelf tools trumpet the volume of API-connectors they offer, rather than ensuring the API-connectors are pulling the right data for clients.

Products not solutions

These companies are focused on building self-serve businesses models rather than implementing solutions that work for real customer use cases. You are left to do the dirty work on your own.

Effective customer analytics requires automated data integration

To get full visibility of your marketing performance, you need to integrate data from multiple sources: advertising, web analytics, payment, e-commerce and CRM platforms. The biggest e-commerce players have built this infrastructure. However, to build this correctly specialist skills are required in data engineering, data modelling and data analytics.

It is extremely difficult to build and maintain this infrastructure

Complex configuration

Correct configuration of your advertising, web-analytics & e-commerce platforms is complex. Most companies do not have the correct set-up in place to facilitate a full look through from first-click, to first purchase, and beyond.

Data structure

Different platforms & APIs structure data in vastly different ways. Integrated data must accommodate these differences today, and into the future.

Edge cases

A multitude of edge cases need to be accommodated to get data to join correctly. With every new implementation of our solution, we learn more about the challenges in this area, which you can benefit from if you outsource this problem to us.

API updates

APIs regularly update. Even small updates can break data pipelines and require intervention. When this happens, marketing teams typically log requests for help from the engineering team. However, engineering teams are typically building product features and marketing teams often get left behind.

Maintenance is not the best use of precious engineering resources

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