When two advertising giants, Publicis Groupe of Paris and the Omnicom Group of New York, recently announced their merger, they cited the need to combine forces, in part to master the power of “big data” in the marketing and advertising worlds.
But even at the new combined company’s size of $22 billion in revenue, it is still smaller than Google and its $50 billion in annual revenue, derived mostly from advertising products.
Big Data is made up of structured data, the ordered type that you can download into a spreadsheet, and unstructured data, which is generated by the terabyte daily by social media, for example.
Publicis chief Maurice Levy cited the explosion of Big Data and rapidly changing consumer behavior (e.g., smartphones and iPads) for the need to shift gears quickly. The companies painted a rosy picture of the merger, but I suspect that there are some very scary numbers showing up in their revenue projection spreadsheets to induce such a rapid move.
We’ve heard a lot about Big Data, and it means very different things in different industries. In the advertising and marketing category, the best definition is: The ability to analyze large data sets to detect meaningful patterns and actionable results.
Big Data is made up of structured data, the ordered type that you can download into a spreadsheet; and unstructured data, which is generated by the terabyte daily by social media and other sources.
An example of structured data is a geographic report we download for a client that shows the geographic source of client website traffic and lead generation or sales activity. By applying analysis to the data, we can identify the best-performing regions, and increase our presence in these regions.
Unstructured data, such as the words in tweets or Facebook posts, may also be clustered to derive trends and rising topics to help guide marketing or reputation management programs. Nestle, for example, has an around-the-clock Digital Acceleration Team based in a multi-screened room monitoring and responding to social media mentions and trending topics about its brands.
Big Data may also be effectively used to go small – to go one-on-one with consumers. How so? The fashion marketer, Gilt Group, uses its five years of member data to daily send out 3,000 versions of its messages to consumers, from intelligence based on shopping preferences, sizes, and more.
Here at Altitude, using remarketing audiences, for example, we are able to direct targeted ads depending on which part of a client’s website a potential customer has visited, and whether or not they have purchased a product or completed a lead form. Remarketing audiences also create a marketing asset – a targeted, actionable database – for a company where there was none before.
Big Data collected and housed by companies such as LinkedIn and Facebook also gives us the ability to target highly detailed potential customer profiles through pay per click advertising.
At Altitude, we also create our own actionable data in highly niche markets, particularly in the B2B realm. By running PPC test campaigns in Google and LinkedIn, for example, we create our own database of keywords and ads, as well as key geo and other information that may not exist anywhere else.
Now that you know a little more about Big Data, a key takeaway is that you don’t need to be a big firm to take advantage of its benefits. Creating your own data, and using data compiled by giants such as Google, LinkedIn, and Facebook will take you a long way down the path of putting Big Data to work for you.
