One of the key currencies in online marketing is data. Every tangible action a consumer takes is trackable, providing complete visibility over customer journeys and purchasing patterns. While it is difficult to attribute the success of offline campaigns to a particular advert or advertising campaign, with online we are far better placed to understand t he influence each touch point has upon a purchasing decision. The performance channel is no exception.
Affiliate networks are able to see the affiliate touch points within a customer journey, but this only tells part of the story. Where the piece becomes more compelling is when additional data from advertisers and agencies is pulled in to see the complete online user journey. This starts to build a picture of how each of the various channels is involved in the path to conversion and the influence they have had upon a sale.
Additionally, data from advertisers provides insight into customers; whether they are new or existing, how frequently they return, the products they are purchasing and their lifetime value.
With such vast amounts of data being readily available it can be difficult to effectively identify which elements are most relevant. Previously I looked at how data can be used to understand the value of the performance marketing channel and in this post I will be extending this to see how successful use of proprietary and additional third party business intelligence tools can help analyse data as well as present the findings in more meaningful ways.
What data is captured?
As mentioned above, affiliate networks capture a significant amount of data. While this will typically relate to the sales generated and the publishers who delivered them, there is a considerable amount of additional data captured. For example the products being sold or the voucher codes redeemed against a transaction can be recorded. Additionally geographic information will be stored such as where your publishers are from and the regions they are generating sales from.
The rise of m-commerce has also seen the way consumers are accessing the internet change significantly. The device being used will also be captured so advertisers are able to understand how consumers are accessing their site. Click to sale, or latency times, impressions and average order values also help flesh the story out. More sophisticated use of data can enable advertisers to gain a true understanding of their publisher base and the customers they are converting.
In turn this will allow for a more effective promotional strategy to be rolled out, with advertisers not only knowing the publishers that are driving sales but those that are driving valuable sales, where they are coming from and through which device.
From Account Managers to Analysts
While business intelligence tools can be sophisticated pieces of software, they provide a simplified way to drill down into the data to really understand the nitty gritty. This empowers account managers to gain a greater understanding into the brands they are working with and their position within their sector.
With the provision of a benchmarking tool based on the data available from any given sector, account managers can identify how their clients compare to others within the same sector as well as being able to identify where the growth opportunities lie.
It is also possible to benchmark across the devices that consumers are using transact. Account managers can use this information to aid recruitment of publishers successfully driving mobile acquisitions across similar advertisers for example.
With the data being put in a simpler form to analyse, account managers are able to essentially become analysts and provide greater programme insights for their client base.
Visualising Data
Business intelligence tools can also help to visualise data in a more meaningful way. It is possible to move away from standardised charts and graphs and really present the data effectively. For example, maps can be utilised to highlight where publishers are signing up to the programme from, while size and colour can be added to charts to easily identify the most profitable publishers or products. When looking at data in Microsoft Excel the formatting options can be limited and there are restrictions in how the data can visualised.
Flexibility of Reporting
Another restriction when using Excel for data analysis is the limit on the number of rows of data that can be added as well as the speed in which it operates. A suitable business intelligence tool will allow for significantly faster and more flexible reporting. Data sources can be easily combined and parameters can be put in place to help with the analysis.
With an increasing amount of data being captured the opportunities for reporting and benchmarking are endless. With a sophisticated business intelligence tool in place, it is possible for advertisers to add extra layers of insight into the performance channel, transforming both their understanding of their campaigns and their key publisher relationships.
