IS BIG DATA AN ACTION OR INSIGHT?

Amante Inc

New Member
Today, marketers have no shortage of data, but if they use the potential of big data to the full?

Digital advertising industry is literally drowning in information flow, "sensational" news, official comments, and reports on the recently launched startups - one way or another associated with big data.

In the theory big data is a miracle cure for reducing the cost-per-thousand impressions and increasing profits. But in practice, working with Big Data very often turns into a pile of wasted time and efforts. Why, you ask? And because the vast majority of start-date companies operate without a comprehensive plan. In addition, many of them are experiencing acute shortage of tools and qualified staff, who could use the data effectively.

Of course, no one offers brands, agencies and publishers to abandon the use of big data and return to the polls of users and contextual targeting. We just need to distinguish between action and insight. Companies need to articulate key performance indicators, to model them and to build their tactics on the basis of the KPI. This approach to the use of big data is called insight. Many data providers and agencies provide brands with this type of metrics. Insights derived from the processing of data on target audiences, are widely used in various fields of e-commerce by brands and help make the right decisions with respect to the product sold, gradually increasing its profitability.

In many articles and conferences that focus on big data, much attention is paid to the so-called 1-2-1 marketing. This is the most direct and targeted interaction with each client. For many brands communication with the consumer at this level is still a utopia. So what to do in order to meet this high bar?

▪ Volumes. To reach out to the consumer we must have sorted data at the very beginning of the campaign. Many brands have information about existing clients, but tend to experience significant shortage of unique and informative data on 99 percent of potential customers. However, neither publishers nor brands are able to cover the market so that develop a strategy with their own means. To do this, they need interaction with companies, which help generate user profiles, collect efficient insights and, ultimately, make the connection with the customers the highest value.

▪ Knowledge. Let's say, at the expense of your own resources or through partners you managed to collect and process enough data and received insights you need. Next you need to turn those insights into effective actions and for that you need specialists with a certain set of knowledge and skills. Construction of models for reporting and analysis of data is the whole 'science', but the application of these models and determination of the optimal way to use them to get the result requires a separate set of knowledge and skills. Modern media advertising ecosystem is quite complicated to use and requires skilled personnel. 1-2-1 marketing - both in global terms and within a particular market - is impossible without qualitatively trained specialists.

▪ The wide reach and global presence. In addition to the knowledge and experience it is crucial to have access to HQ inventory for each market segment. There are three pillars on which the interaction with the customer rests: creativity, audience and context. To maximize the results of a 1-2-1 campaign, you need the right inventory. Many argue that resources of open ad exchanges are more than enough, but experience shows that the use of data to optimize inventory at different stages of the study of a potential customer, gives a colossal impact on the performance of engagement and conversion. Therefore, the choice of major brands increasingly falls to private auctions and premium platforms.

Described above situation is only the tip of the iceberg. The full potential of big data is disclosed only in the case when you have developed a clear plan for the use of this data, you have chosen the right partners, you have an understanding of key performance indicators to track the results. Without this big data is no more than an endless and useless digital stream of ones and zeros.
 
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