The National Gallery Company Limited (NGC) is the trading arm of the National Gallery. Its primary purpose is to generate income for the National Gallery and the National Gallery Trust through a number of commercial operations, including the Gallery shops within the gallery and through the website.

The National Gallery Company

The Problem

The National Gallery Company wanted to better understand their customers’ lifetime buying habits through the website along with what products were being looked at, added to basket and then bought or abandoned. This information could then be fed back to and used by the buying team to ensure the right products were being stocked at the correct volumes.

The Solution

After getting a detailed brief from The National Gallery as to what questions they were looking to be answered it became clear there were two angles that needed to be covered, the onsite product interaction behaviour and customer lifetime buying behaviour. The first was available through their Google Analytics and for the second The National Gallery exported out all their customer data from their CRM system, which was then imported into the 4Ps Marketing data warehouse to be analysed.

Using the detailed Google Analytics event tracking The National Gallery already have in place we could map out the onsite journey from a product being added to the basket, through the checkout funnel to a successful purchase with all the drop off points in-between. This showed us how successfully people were moving through the sales journey on different devices plus identifying which products were being added to the basket and then bought, or not, and how this differed by product type and price point.

National Gallery Example Output

Looking at the CRM data we identified how often people bought, where in the world they were, how much they spent and what they bought. We were also able to tie this back to Google Analytics using the transaction ID as a common parameter. This enabled us to see the marketing channels and devices people were coming through on when buying online throughout their lifetime.

Challenges

There was a lot of data to analyse going back many years therefore it was crucial we had clear and specific questions to focus on answering so the time was spent efficiently and effectively in pulling it all together.

Results

As a result of the findings The National Gallery’s buying team can now make much more informed decisions on what types of products they get in and whether they need to adjust any price points at all. There are also potential quick wins in better targeting segments of their customer database to either increase purchases amongst already active customers or reactivate dormant ones.

National Gallery Example Output

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