Programmatic & Big Data Nerds: It's Marathon, Not Sprint

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.

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.


2 comments about "Programmatic & Big Data Nerds: It's Marathon, Not Sprint".
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  1. Denise Colella from Maxifier, November 6, 2014 at 11:44 a.m.

    Great article, Skip (and timely.). Another parallel I see is the use of pacers--too many premium players leave the fate of performance to their adserver, trusting their systems to manage 100% of their optimization and decision making. When it comes to premium, there is too much at stake to allow for simple campaign specific optimization--changes should be made understanding their effects in the greater inventory pool. Just as runners cannot trust a random pacer to guarantee a PR (what is their strategy? consistent pace or negative splits?) premium players should control their own strategy and optimization tool if maximum performance is the goal.

  2. Skip Brand from bbd (branding big data), November 7, 2014 at 9:42 a.m.

    Denise (congrats on NYC marathon),
    I think you are correct in the overuse use of pacers, consultants and technology partners. Premium brands need validation, brand lift/recall, time spent, but most important BRAND FIT (only judge fit by brands big data, strategy and KPIs). Your advice is perfect to have a personal best running as well as with programmatic brand advertising campaigns. Taking control of the strategy and working together to optimize and maximize the goals is key. Thx.

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