The goal of any form of advertising is to create the perfect mouse trap, which is an analogy you’re likely to hear during your time spent in the industry. Amazon is the best example of this, with the ability to show us products we didn’t even know we wanted all over social media. Scroll through Facebook or Instagram, even if you haven’t been to Amazon in months, and you’ll find new products to indulge in.

The cornerstone of today’s online merchandising strategy involves this kind of predictive groundwork: showing customers what they want before they even realize it. How have these systems become so robust? The answer is simple: a vast amount of data at play.

Data is the First Step

Google Analytics represented a novel idea when it debuted in 2005. It represented customer data accessible to small business owners for the first time and was a major leap forward in understanding the behavior of your customer base. Today, the system is quite robust, offering a variety of reporting to determine what people are doing when they land on certain pages. Good marketers use this freely available data to make educated guesses about which channels are working best.

Essentially, data storage is inexpensive and cloud computing has exploded. Companies who aren’t leveraging this powerful data are at risk of being left behind.

Location is Key

Just like real estate, or even billboard advertising on a busy street, advertisers are looking for the next source of high traffic for their website. Smart marketers are micro-analyzing potential publishes to try and determine which sources send the most traffic, and how that traffic translates into conversions.

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With this data, marketers can figure out which websites people visit and where their next buyers are likely to come from. There are also more outlets to purchase advertising outside of television, and major search engine providers. Smaller ad companies purchase space wholesale on blogs and provide affordable alternatives for micro-targeted ads.

Forecasting to the Extreme

Sales forecasting relied on historic figures and anticipation of demand to make a somewhat reliable goal for oneself. Today, there is a deluge of information to forecast everything. More connected devices are gathering information about consumer behavior, such as which commercials they might pause for on a DVR or which videos they might spend the most time viewing online.

All of this data provides clues to what consumers want to see, even if they are not consciously aware of this fact. Marketers can also cross these channels to see the impact social media has on how someone watches television or a video on YouTube.

Better Data Crunching

Tons of data also means a lot of noise, and it can be difficult to figure out which figures offer real value in the overall strategy of your business. Today, there are a variety of analytics applications available to site owners that track everything from video interaction to social media contests and the effectiveness of random giveaways.

Crunching data with better efficiency helps marketers identify the key stats that matter to a particular industry.

Not Without Risk

So much data can compel marketers to view customers as one-dimensional objects. It’s easy to play a numbers game, especially in eCommerce where public interaction is not a requirement. Understanding one’s customer base is essential for success in the industry. Boiling your business down to numbers hurts you long term, as you fail to recognize budding trends that numbers won’t show you.

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