Pushing Out and Pulling In The Right Data to Grow Your Brand Online

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Brands need to think more about the data they’re pushing out with the big aggregator websites who are increasingly controlling the majority of website traffic, as well as the data brands are pulling in to manage decisions, or risk being left behind.

Way back in September of 2012, Tom Anthony, Head of R&D at Distilled, wrote a prescient post The Role of APIs in the Future of Search. In it he makes a bold statement: “I believe that over the next 10 years there will be a huge decline in the number of users visiting websites, and that APIs (and structured data) are going to play a pivotal role in that shift.” What he meant by that is that big “aggregator” websites like Amazon, Google, and Facebook are increasingly controlling the success of your brand (not your brand’s own website,) so how you both share data with (push) and use data from (pull) these aggregator websites will determine your brand’s success.

Indeed, your success in the future will be less about your webpage and more about:

1) How your data is pushed out and integrated through Application Program Interfaces (APIs), data feeds, and structuring data into the broader ecosystem of the internet

2) How you pull in and make use of external/internal data in your marketing campaigns.

Pushing Your Data Out

Have you noticed the ever-increasing trend in search engines where the answers to your questions are at the very top of the search results page before the results themselves? Maps and directions, exchange rates, translations, weather, flight price comparisons, and the list goes on! Search engines are become more than just gateways to answers, but providing the answers themselves. This is reducing (and could eventually eliminate) the need to dig further on many topics.

The same is true for online shopping (product searches): Amazon.com, the prototype for this model, is the full package – everything from product discovery and tailored suggestions, to comparisons and reviews, to purchase and fulfillment. It’s a one-stop shop for ecommerce. And a host of comparison shopping engines (CSEs) including Google Shopping, Bing Shopping, Pricegrabber, Shopzilla, etc. are undoubtedly working towards the “Amazon” goal of vertically integrating all phases of the online shopping experience. Case in point: Google Shopping Express is Google’s first production model. This isn’t a surprise as all of the technologies necessary to make this possible are mature – companies need only plug the pieces together.

As these changes in search and ecommerce gain traction, consumers alter their habits and form new user conventions and expectations. That’s a force to be reckoned with, so it’s time to learn how to join or die!

The key to understanding all of this is that both these changes in the search results, as well as in ecommerce, all require more data than previous iterations. And if you’re to benefit, they require more of your data.

Of course, on the search side of things, part of this data acquisition effort doesn’t require your participation. Search engines have made huge strides in their ability to pull in and process information from across the web and beyond. But if that’s all there was to it, we’d have a level playing field for everyone. The reality is that the power players (and you) can push much of your data out just as well as the engines can pull! By proactively submitting/packaging your info with structured data and other means, you should realize a clear advantage.

Adding structured data to your website gives search engines a “guided tour” of your site’s content and helps them to come away with a better understanding of everything from how your site should be categorized, to searchable transcripts of your videos and more! Structured data is just what it sounds like – information (data) that you add to your web pages using a specific syntax (structured) tied to the data you’re augmenting (e.g. videos, images, products, etc.). To implement, you just need a firm understanding of the syntax and the ability to edit your website code.

But in contrast to something relatively complex like structured data, even something as simple as having a clean robots.txt file (link to http://www.robotstxt.org/) at the root of your site and an XML sitemap submitted to Google Webmaster Tools and Bing Webmaster Tools (covers both Bing and Yahoo!) can move you forward. We frequently talk with organizations who are missing these basic elements of a search-engine-friendly website. These simple files quickly orient web crawlers to what you deem important on your site. Just for fun, check to see how your site is fairing: for the robots.txt file, just append “/robots.txt” to the end of your domain in a browser (e.g. example.com/robots.txt). To find your XML sitemap, add “/sitemap.xml” (e.g. example.com/sitemap.xml). Let us know what you find!

Now, moving on to more details regarding CSEs and Amazon.com, you’ll need to understand a little about data feeds, or more specifically, product feeds (the data that powers these sites). It’s a pretty straightforward process to push your data into these environments – very similar to managing an ecommerce store or an advertising account, since they’re essentially a mash-up of the two. But to reiterate the point made earlier in this post, there are surprisingly few companies that have made the effort to increase their visibility in these channels, let alone optimize them! To get off the ground with a knowledge of the basic setup involved with product feeds, check out our post, 20 Steps To Setup And Optimize A Google Shopping Feed.

We’ve seen really strong results with both Amazon.com (when done right) and most CSEs for companies/categories where consumer demand is strong. Because these are search-based channels, they are very effective at harvesting demand. But for the same reason, don’t expect these channels to perform well for creating demand/awareness. If you find yourself in that situation, we’d steer you towards Facebook advertising or a smart display ad program.

Pulling Data In

We need to shift gears a bit now – this section is not a simple flip of what we’ve covered so far as you’re probably not in the business of aggregating data. Rather this section will specifically cover leveraging data-driven advertising opportunities that are ready for you to plug into.

For most advertisers, pulling outside data in for marketing use is low-hanging fruit. We’re simply talking about targeting options that you’re not currently taking advantage of and how this additional information will allow you to better segment your audiences – driving better performance for each dollar you invest. Of course, this isn’t a new concept, but what IS new and exciting are the kinds of data that are currently becoming available as the delivery mechanisms mature and move down market.

In this section we’ll also talk about pulling in data that isn’t external, but internal – the data opportunities that are inside what you’re already doing, but that haven’t yet been applied to your marketing campaigns.

So, let’s go through some of the big buckets: analytics, awareness-building channels, and channels for harvesting demand.


Many companies don’t do everything they could to leverage their internal data with external entities (pushing data out), so it’s not surprising to see the same issue when it comes to internal data – this, too, needs to change.

Collecting and analyzing data on your website visitors can reveal a treasure trove of insights that you can then apply to 1) your marketing efforts (both in the setup stages and in optimizing the performance of campaigns once launched), and 2) to the site itself with ongoing conversion optimization (e.g. making the site easier to use, removing bottlenecks, etc.).

And with something like Google Analytics, a free site analytics package that’s exceptionally powerful, there’s no reason not to be collecting and analyzing this data! Unfortunately, few organizations get even a fraction of the insights they could because of configuration errors, or they’re simply too busy to dig deeply. So it’s of paramount importance that you correctly track and analyze visitor data through your analytics package. Here are some things to consider:

  • Do you own your account and have full access?
  • Are you using the most current version of Google Analytics (the Universal Analytics tag)?
  • Are you setting up multiple views of your data? e.g. Do you have a view that filters out internal visits?
  • Are you keeping your path-to-conversion reports clean with referral exclusions?
  • Are you tagging all of your campaigns with tracking parameters?
  • Have you set up goal conversions?
  • If ecommerce, have you set up Ecommerce Tracking?
  • Do you try to tie revenue/profit back to spend?

From this list of basic questions, we hope to expose the purpose and benefits of all of this data that you can pull in with analytics and apply to your advertising: Find the winners, cut the losers, and make better choices with your media mix.

Awareness-building channels

Earlier, when we were talking about search-based programs (like AdWords or CSEs) and how they typically do a poor job of creating demand or awareness, we hinted that Facebook would be a better solution. One of the biggest reasons for this is that Facebook has a TON of data to work with and they package it very nicely for all sizes of advertisers. So if you know who (and “who” means data – likes, interests, demographics, etc.) would love your product or service, Facebook provides you with a fantastic platform to target them and build awareness with.

For a great example of how the accessibility of targeting data is moving down market, check out our post on new developments in advanced Facebook targeting.

If you have bigger budgets, the sky is the limit when it comes to awareness building. But we’re not necessarily talking about fancy ad formats here (although that often comes with more “flexible” spending) because a fancy ad with stupid targeting (data) is just as bad as an ugly, bare-bones ad with stupid targeting. The data makes all the difference when it comes to performance! And that’s the cool thing that larger budgets allow for – more and better data!

Everything comes at a cost and you do have to reach a certain scale before the incremental cost for data is justified. For example, many platforms that allow you to serve your own ads (important for getting impression-level insight) and apply various data overlays from various sources to your targeting can have minimum monthly ad spend requirements of well over $30,000! It’s big business. Sometimes that a per-advertiser minimum, but in some situations you can aggregate your demand with other advertisers to get access (separate campaigns, of course) – and that can be a key reason for working with and advertising agency.

But big spending isn’t a requirement for big success – you just have to be smarter with what you can access so that your investment goes as far as it can. Once the model is proven, then scaling up is easy.

Demand-harvesting channels

This section will now bring us full circle – back to search and the CSEs. But similar to our discussion on analytics, the benefits you can gain from pulling data in to your demand-harvesting or search-based campaigns aren’t necessarily from how you apply external data, but how you apply internal data. And oftentimes, this internal data is sourced from the feedback loop of testing, watching performance, learning, and testing more. In other words, you have to track and take advantage of the deep data that’s natively accessible in the platforms.

For example, let’s take your paid search campaigns: The “data” that you should pull in to your campaign optimization efforts isn’t always numeric in form as with impressions, clicks, conversions, etc. But it’s the stuff that’s causing your stats to turn out the way they are. Things like the actual search terms your keywords are matching for, the flow of your ad text to your landing page content, your targeting and network settings, your ad positions, etc. etc. – All of these “soft” data points are ready to be explored and exploited if you’re ready to dig into them. These are the inputs, not the outputs; so the better the data – of all types – that you can bake in on the front end, the better your results.

To an even greater extent, these kinds of “soft” data points are important to understand when it comes to working with comparison shopping engines. Optimizing campaigns in this channel is even more reliant on the test/learn cycle and the insights you glean there because – as with organic search – the factors used to rank competing products are kept pretty close to the vest. So again, constant testing and tweaking will be your best bet for optimizing your CSE campaigns.

Pushing Out and Pulling In At The Same Time

In the last couple years, the ability to reach out to your target online using a mix of internal data (addresses, email, names, etc.) and external data (typically provided by your ad vendor/platform as a means of mapping your data to online audiences) has made a move down market to smaller advertisers. This technology, known generally as CRM retargeting, can deliver impressive performance given the right data sets. Just think about it – you take your data (typically an export from Customer Relationship Management software or an offline prospect list) and match it up with outside data using a primary key of sorts to target advertising in new, highly segmented ways! This is a great fit for that empty position in your marketing mix just below your broader awareness-building/prospecting efforts.


Understanding both the push and pull of data, and implementing strategies to capitalize on these new data pathways, means your brand will be able to work with, and not have to swim against the tide formed by these big data aggregator websites.

At SmartClick, we’re already working to bring the push and pull of data using top-performance marketing technologies down market so our clients can give their larger competitors a run for their money. If you’d like to discuss opportunities more specific to your category, we’d love to chat!

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