While understanding and optimising how your marketing pounds and dollars are allocated is always good practice, when the shadow of recession looms firms must inevitably work harder to win customers. Therefore knowing where your customers come from and which are the most valuable becomes essential for business continuity, let alone growth.
To achieve this commercial goal, QuantSpark regularly works with clients to unearth insights from their marketing data that drive revenue and cost optimisation. Our teams can work end to end, ensuring our clients are collecting the correct data to support their objectives, integrating GA with their systems and structuring models correctly.
Organisations can create insights from two sets of data: user acquisition (data about users before they visit your site) and user behaviour (data about users while they’re interacting with your site). These insights can range from characteristics such as age, gender, and interests to how long they spend on your website in each session.
Google Analytics outputs this data to a set of visualisations and charts to make it easier for the user to understand and interpret the information. The tool provides 20 custom dimensions including session ID, client ID, and user ID.
Although custom visualisations may be created using these dimensions, as with many similar analytics tools much of this data is typically high-level information which alone doesn’t always provide the quality of insight that is needed to drive business decisions.
Our approach combines the data GA provides with other sources to build a more complete picture of how our clients’ customers interact with their business. For example:
Judging ROI from marketing campaigns are still a hard thing to do and in today’s world almost impossible to do intuitively.
Google Analytics is a key tool to building granularity into a business’s marketing operations and understanding exactly how each marketing dollar is spent.
Businesses need well structured data to make the most of this tool and QuantSpark is ideally placed to support.
By tracking customer sessions before purchase, we can begin to accurately allocate cost of acquisition (CAC) – in other words the marketing spend required to win a purchase.
Linking transactions with user ID allows us to see purchase size and type of client – providing a foundation to help us identify what further revenue we can get from this client. This forms a key part of the customer lifetime value (CLTV) metric.
In turn, we can get a more accurate representation of the ROI for advertising campaigns by using the lifetime value vs cost for these marketing channels.