Everyone
-- especially runners -- loves the New York City Marathon. The same passion can be felt by programmatic and data enthusiasts. Programmatic buyers and sellers are constantly sprinting for new
inventory, the latest technology, reducing costs, fighting for more control, transparency, and measuring attribution. Data speed freaks are quickly aggregating DMPs and building cookie pools while
wrestling with third-, second-, and first-party data.
Similar to planning to run the NYC Marathon, brands and publishers need to determine goals, KPIs and business objectives. Brands that do not
train (or in the case of programmatic and big data: do not test, learn, model, and explore) will not find success or finish strong in order to move from being simple joggers to full-fledged
runners.
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There are five areas in the marathon of programmatic and big data that will help brands enjoy the run and finish strong.
Actionable Insights
The fashion in
which a brand starts is many times the same way a brand ends. The expectation for data-driven programmatic is high, but the majority of marketing leaders believe the real value is to make intelligent
business decisions and foster a data-driven organization. It is important to make relevant data more consumable without relying on data scientists. By doing this, the data is consumed easier and the
brand can develop methods, strategies, and testing directly related to goals.
Business Intelligence (BI)
Business intelligence, visualization, and simple infographics help with
data discovery and problem-solving through common-sense analysis. BI tools help visualize information. By turning it into an infographic or a landscape, marketers can then explore with their eyes and
map out the problems to be defined, if not solved.
Data Optimization and Algorithms
Programmatic data investments must lead to media optimizations for both big and small brands
with any size budget. For many players in big data, running programmatically means that the systems or technology, installation, and testing all run according to plan. In more advanced deployments,
big data success is defined by outcomes like insights, solutions, improved marketing, and customer acquisition. A consistent data model keeps the brand moving forward by solving smaller problems and
finding bigger opportunities.
Progress, Not Perfection
Marketers and brands can either get buried by the avalanche of big data or use partners and technology tools
to continue to make progress. Reducing scopes allows the brand to celebrate wins like reduced media costs, double the amount of impressions and viewablity, and increase optimization. The devil
is in the details. Getting analytical insights in real time is important, as well as uncovering patterns and relationships that were too costly to discover or track previously. Many find the brands
that can apply big data to help with paid, owned, and earned media to be progressing -- despite not having confidence that everything is perfect.
Have Something Left in the End
Successfully implementing big data and programmatic is stressful. This includes injecting the complexity of real-time bidding, programmatic direct, guaranteed programmatic, private and public
exchanges, as well as boosting brands businesses’ speed of thought. The brands’ technology partners, agencies, and big data and measurement companies are pouring on the investment to
ensure programmatic and data are producing ROI. The goal of buying the right impression at the right time and price for premium programmatic is getting easier due to data-driven decision-making.
Programmatic and data nerds will find lots of ways to get started and need plenty of helpful advice to keep going, but anyone can get it done through leadership, pig-headed determination,
discipline, training, and perseverance -- just like finishing a marathon.