Automating Everything That Should Be Automated

How much time do standardised, routine tasks take your team to do? Whether it is chatbots or filling reports: if its automation is viable, delaying it costs more.

In September, DoubleVerify, a software platform for digital media measurement, data and analytics, surveyed 300 publishers and SSPs on the challenges they faced amid the pandemic.

47% of respondents are late on billing their partners, as they lack resources to process data. As a result, payment times increase, which impacts budget planning and business development.

And 80% do not optimise inventory performance and revenue as they spend “too much time manually processing inventory performance and revenue data”.

Day after day, publishers download, merge, and filter data only to realise once again that they cannot possibly make time to assess the state of business and re-plan inventory in peace since they need to download, merge, filter, over and over…

Have you recognised yourself? Then you know that such problems did not arise due to a pandemic. It’s just that now incomes have decreased drastically on top of being irregular.

But companies don’t have to drown in data. Downloading and sorting ad server reports, calculating and filling out invoices, and generating a basic report - a regular script can handle all these tasks. A small automated system would save the team a lot of time and effort that could be better used for business growth.

Automation is also needed with substantial cash flows when even a 5% growth results in an additional five to six-digit figure to monthly revenue. The increment can be achieved by optimising the use of resources and requires tools more sophisticated than a simple reporting algorithm that fills in a template.

Large publishers face such a volume of data that cannot be handled manually with efficiency comparable to machines. That is where Big Data analysing tools are needed.

Advanced analytics and monitoring, detailed reporting, forecasting – automate tasks that demand the utmost accuracy, whether by in-house solutions or integration with dedicated platforms.

By building a tool from scratch, the publisher retains complete control over their data and can customise its configuration to their business specifics. But developing advanced analytics systems goes beyond the publishing field and often requires R&D, with all the costs and risks entailed. Therefore, in most cases, a vendor with a tried and tested product is a better choice.

Svetlana Petryanina
Svetlana Petryanina

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