Analyzing the Data Your Customers Provide

Analyzing the Data Your Customers ProvideIt is no coincidence that when marketing professionals and industry leaders talk about Big Data they use words like deluge, ocean, mass, and eons. Words like trickle just don’t work to accurately describe the data sets produced by Big Data analytics.

Given the enormity of the data sets that companies find themselves inundated with, it might not come as a surprise that, according to a recent Oracle report, 94% of executives note that their companies find themselves analyzing more data than they were two years ago.

Further, 93% of executives (according to the same report) believe their businesses lose money as a result of being unable to leverage the information they’ve gleaned from Big Data software. It should be clear, then, that it’s not enough to simply collect the data: Businesses and organizations need to analyze this data in order to put it to work for them.

When you embark on a Big Data project you are essentially asking your data to tell you a story. The story might be one of churn or conversion rates, or it might be predictive in nature, telling you when your customers are more likely to want more of product X and less of product Y, for example. Big Data makes big promises, but in order to garner results, businesses need to listen to the narrative the data tells them, even it forces some uncomfortable decisions.

One of the most immediate ways to put your Big Data to work for you is to use big data analytics to improve personalization strategies. (Consider Amazon’s “Customers who bought this item also bought…” strategy as a case in point.) Here, we look at several interesting and effective ways companies and organizations have analyzed Big Data in order to improve personalization.

Mine Social Media Data to Personalize User Experience:

Ask any artisan where they sell their wares online and they’ll likely send you to Etsy. A giant in social commerce, Etsy showcases more than 80,000 shops, which translates to upwards of 15 million unique items. However, even with such a large presence in social commerce, Etsy still faced a challenge: While Etsy itself may have become a household name, the company still needed to find a better way to bring attention to the individual sellers that call the site home. In order to do this, they reached out to Pinterest, believing that Pinterest’s visual nature was a natural complement to Etsy’s sellers.

The Etsy editorial team first made inroads by increasing their brand presence on Pinterest. This involved daily Pins of Etsy products and a careful curation of their Pinterest site. Currently, Etsy has 75 boards on Pinterest, including an Editor’s Picks board, Etsy Weddings and Cool Spaces. The end result is a well-organized, clean, aesthetically pleasing visual smorgasbord of Etsy wares. The company also instituted a guest pinner program, where design celebrities like Martha Stewart and Camille Styles pin items that they love. Viewers can then comment, and of course, re-pin items to their own boards. The guest pinner program is an ideal way to diversify opinions on Etsy’s Pinterest page, and to utilize art and design leaders to shape tastes and opinions.

Etsy noticed an increase in pins after upgrading their Pinterest page, and so elected to add a “Pin It” button to their product pages. The Pin It button makes it simple for Etsy users to Pin items they like; products pinned from Etsy then show up with full artist/designer attribution on Pinterest, making it simple for viewers to click back over to Etsy to make a purchase. In addition to making sales easier, the Pin It button helps Etsy as well as individual sellers understand what viewers like and don’t like, via frequency of pins and re-pins.

Use Personalized Ads, Products, and Services to Improve User Experience:

An inefficient and outdated ecommerce platform was causing successful sporting goods retailer Anaconda Sports to lose sales and irk customers while they were at it. The company understood the problems with their ecommerce platform stemmed from the fact that:

• The site did not store customer information, forcing even repeat customers to enter their information multiple times, making the user experience clunky and redundant.

• Because the site was not collecting customer information, it could not help the business provide a unique buying experience for each customer.

• The site was not enabled to allow customers to track orders online. Customers with questions or concerns about an order had to call customer service in order to receive an answer to their query.

The solution to Anaconda’s problems turned out to be Amazon’s Webstore, which helped them transform a clunky, anonymous site into one that is optimized to provide a personalized experience for users. It stored visitor information, and tracked purchasing history to provide reasonable product suggestions. Opening an Amazon Webstore allowed Anaconda to retain their own identity while partnering with data whiz Amazon to implement an ecommerce site that provided visitors with a more personalized shopping experience.

Perhaps the largest upshot of working with Amazon is that Anaconda now is able to place Amazon product ads. This means that when a shopper is searching for a baseball glove or a basketball on Amazon, they might see an Anaconda ad advertising baseball gloves. Visitors can click on the ad and are taken straight to Anaconda’s webstore where they can make a purchase.

Since partnering with Amazon, Anaconda’s Director of Ecommerce reports the company is “reaching more shoppers, generating more revenue at a lower cost-per-click, and earning a much higher ROI.” Having the ability to put large corporations’ Big Data knowledge to work could be huge for smaller companies in the future, allowing them to target niche consumers while still maintaining their own brand identity and independence.

Use Big Data Points to Predict Behavior:

The Point Defiance Zoo and Aquarium (PDZA) is one of the largest outdoor attractions in Pierce County, WA. Located in the rainy Pacific Northwest, PDZA had serious weather issues to contend with: Depending on the weather, visitor numbers can fluctuate wildly from day-to-day. This made it hard for the zoo to predict how many staff members need to be on hand, how many programs to offer, how many tickets they could reasonably expect to sell, etc.

The PDZA understood, of course, that rain is a way of life in the Pacific Northwest, but wanted to gain a better understanding of the ways that weather impacted ticket sales and customer services so they could better forecast visitor numbers and staffing needs in the future. The zoo already had a lot of data, explains PDZA’s Donna Powell: “We already had a very robust point-of-sale [POS] system in place, which was managing most of the data we needed to assess key metrics on ticket sales and attendance. However, without the tools to extract that data, analyze it and present it to our business users in a form that was easy to understand, its value was limited.”

To Remedy this, PDZA worked with IBM Partner Bright Star, who helped them develop strategies to leverage the data they already had to answer their questions.

Matching POS data to national weather forecasting systems allowed the zoo to quantify what they already knew: When it rains, people are less likely to come to the zoo, but on average, how much less likely are they to visit? Consider this statistic the zoo reports: On a sunny Wednesday, PDZA had 5,000 visitors. The next day it rained, and the zoo only had a scant 1,200 visitors, coming in at a 289 percent difference. This knowledge allows the zoo to tweak services and programs to optimize a visitor’s experience: On a day when they can expect 5,000 people, more staff members are needed, more shows, more refreshment stands need to be open, than on a day when only a handful of people will be around.

In addition to helping PDZA understand the ways that weather impacted their ticket sales for forecasting and staffing purposes, they were also able to correlate ticket sale data with other spending patterns. For example, they found that visitors who bought tickets online were more likely to spend money on retail and food while in the zoo. This knowledge prompted the zoo to up its promotion of its online ticket sales.

PDZA’s Big Data experience demonstrates the ways that Big Data can work to make organizations run more efficiently. The story was always the same: No one wants to go to the zoo in the rain. The only thing that changed was that zoo administrators were able to harness this knowledge and quantify it in order to help the zoo run at peak efficiency, while at the same time improving the visitor experience by tailoring programs and staffing to meet the needs of the day.

The Takeaway:

As a marketer, you are consistently looking for ways to deepen relationships with customers and to improve user experience. Big Data, for so long a treasure trove that only the very largest companies could afford to mine, can help you to do this. Big Data can tell us some important facts about what is and isn’t working – if we’re willing to listen, it can allow us to change the game.

image credit: nationmedia.com

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Innovative Data - Numbers Telling a BIG StoryRob Toledo is Outreach Coordinator at Distilled, aka marketing coordinator with experience heavily focused online. Technologically driven, with a love for SEO, outreach, link building, content creation, conversion rate optimization, advertising, copywriting, graphic design, SEO, SEM, CRO, Google Analytics, social media, creative content…you get the picture. He blogs at stenton toledo

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One Response to Analyzing the Data Your Customers Provide

  1. Robert says:

    Rob, I enjoyed your article. For PDZA, what are your thoughts on why visitors who bought tickets online were more likely to spend money on retail and food while in the zoo? Thanks. – Robert

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