ADM serves Car Dealers, Automotive Marketing Pros and Internet Sales Managers
Social is a hugely exciting space right now. For car dealers and automotive marketers social media gives us, for the first time online, the ability to connect with customers individually, and in a highly targeted, customer specifics defined way.
For automotive search engine marketing (SEM) campaign managers and dealership content marketers it isn't just the various social media platforms but also the data these platforms are set up to collect and provide to auto industry advertisers at all three tiers that is really exciting. So how can an automotive marketing professional make use of what will become the most valuable available treasure trove of automotive consumer data?
Of course, all automotive marketing professionals should be readily adept at applying the data throughout your strategic work, and as part of informing dealers, general managers and key decision-makers. Additionally, and perhaps more importantly, one of the most useful, and relevant uses of social media driven "Big Data" is in helping steer content creation ideas, identifying hot topics of the day and your content syndication strategy.
Big data startups are crawling all over the social space right now, and for good reason. Social data has the potential to unlock vast amounts of insight about OEM brands, specific model lines and associations with specific dealerships. This provides car dealers with vehicle shopper and service customer information that most of us have speculated about for years within the automotive marketing profession, but is only now coming available in a usable format.
Facebook, Twitter, Pinterest, and other social media platforms serve up a smorgasbord of car shopper and service customer info for automotive marketers who have taken the time to learn how to access it and where to find the most useful data points within the reams of data that is provided.
Because of its rich detail and local nature, social media channel collected "Big Data" can help car dealers and automotive marketing pros to build out highly valid audience specifications and the "Perfect Prospect" persona profiling pieces. On top of accurately defining who, a proper analysis pf these data patterns can be an ever increasingly more effective way to inform your strategies for reaching the right automotive consumers at the right time with the right message.
To do that requires an understanding of APIs and some elbow grease, but a lot of the hard work can also be taken out by choosing your social media data collection and mining tools wisely.
Where social data gets really interesting for automotive marketers is in the associations between people and the makes and models they show an affinity for. Increasingly, individuals are Liking dealership, make, model and enthusiast pages. By mining Facebook's Open Graph data you can get some amazing insight into what makes them tick – including some eye opening info about how wrong your previous assumptions can be.
Investing in content isn't cheap. To make the return on investment (ROI) work you must almost guarantee that an idea will work. In practice this is incredibly difficult to do but with access to the right data you can severely increase an audiences' propensity to share and digest whatever it is you want to create for them.
One way to do this is to pull data from key relevant pages across Facebook so that you can see exactly what is being shared.
To give you some idea of the depth of data that Facebook holds about us all, it's worth pointing out the famous example of Austrian student Max Schrems, who requested a copy of all of his data from the Palo Alto, Calif.-based corporation. The result was a 1,200 page PDF that included everything from a field called "last location" to what he alleges was old "deleted" messages, posts and even Poke and IP addresses.
Facebook's true value is in their data and targeting capabilities. Facebook are combining their huge graph of data on individuals with real world purchase and preference data from a number of suppliers, meaning that soon they'll know even more about us than ever before.
If you don't have a suite of tools, it's possible to better correlate that data manually, even without API access. To do that you can use tools such as Facebook's Power Editor & Google's Display Ad Planner, where you can see data based on potential audience sizes for planning purposes.
Analyze the content for the brand in question across all social media pages, and combine this with Google interest sets and other data sources to allow you to identify content opportunities and appropriate weighting. You can then give each brand 1,000 "content points" which are distributed among topics based on their relevance.
This then allows you to identify whether a brand should be focusing on branded content or spending more time on interest led content for example as a first step. The image below shows how this data looks once polished.
In this example the data has told us that for this particular brand (in the alcoholic beverages space) has a social audience that likes "brand content" on page but also engages with celebrity content (see the deeper dive right hand ring for who). This gives you an immediate hook for a content brainstorm, to ensure you have enough of the right kind of celebrity-edge content for the Page.
The data dive can then go deeper still and extract information from both social and AdWords' Display ad group Interest Categories based on specific interests (such as specific celebrities, make up brands, and car makes for instance). This can give you more information about other things your audience is interested in.
To see how Google currently "categorizes" you log in and visit this link. The results are eye opening! This post gives you even more info about other ways you can utilize Google's ad targeting data to help.
Another great and under utilized tool is the search giant's Display Network Ad Planner. Its GDN Research Tool, or Audience Builder doesn't dive massively deeply but provides easy access to data sets around specific interest points. You can work out potential audience sizes based on everything from location and language to specific interests and even sites. It also works as an outreach tool to find the biggest sites in very specific niches.
Again, below is that data in "polished" form for the same brand, showing a huge correlation between them and specific beauty brands. Again, this is great content insight.
As well as mining Facebook, you can also look to existing tools to help paint a picture of your audience and provide inspiration for what they are currently sharing and what makes them tick.
You can get carried away with a lot of this, but through trial and error a fairly simple process will provide the insight you need using the following tools:
As with all data analysis the key is not drowning in too much of it. Take top fives from each category of data (or tool used) as this keeps it simple.
Bring this data into your idea creation meetings. Then follow a strictly defined process to ensure you brainstorm around as many "pillars" as possible.
Those pillars include looking at everything from the content needs of existing marketing personas and keyword opportunities to semantic phrasing and back again. It results in a data-informed strategy that leaves no stone unturned.
Read more at the Source: SearchEngineWatch.com/Mining-Social-Data-to-Create-a-Content-Strategy