Designers are no longer relying solely on a pencil and paper to come up with a great idea. Data is the latest design tool being used to shape better decisions on product development and marketing. Retailers are measuring consumer preferences online and using this data to inform design decisions.
“Companies increasingly understand that their ability to compete is tied to their ability to create and harness value from data, and are seeking new ways to look at big data and beyond,” according Kathryn Howe, senior advisor for the retail industry at Cisco, in its recent white paper, “Beyond Big Data: How Next-Generation Shopper Analytics and the Internet of Everything Transform the Retail Business.” The report revealed that nearly half of retailers globally have big data initiatives, and companies will spend an average of $8 million on big data initiatives in 2014 alone across all industries.
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Research from eCommera found only 23% of UK retailers feel they can quickly make sense of the data available to them to make the right business decisions, according to a Computer Weekly article. Meanwhile, nearly 50% of retailers believe their current business intelligence tools fall short of their needs, with only 16% confident that their data analytics tools provide the organizational visibility they require, the article noted. Further, Cisco’s research reveals that retail has a significantly high potential value to be gained by using IoE (Internet of Everything) to gather store metrics—up to 11 percent, or up to $1.584 trillion in additional net profits.
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The speed of change in today’s digital era is seen perhaps most clearly in the retail sector, where consumers eagerly await the next iteration of tech devices and upgrades. However, “a still-turbulent economy, new selling channels, advanced digital technologies, and increasingly demanding consumers all challenge retailers to find new ways of remaining relevant and competitive,” says Howe. By capturing and digitizing every step of the purchasing decision journey for consumers, retailers can transform the data into usable metrics that will help take the guesswork out of their decision-making.
In a bid to close the gap between content and commerce, retailer Target recently worked with media platform Who What Wear to launch a clothing and accessories line designed using editorial data and user feedback from Who What Wear’s active online community. The collection taps into the most popular street style posts featured on the site, which has more than 200 million page views per month, by using data from passive clicks as well as reader feedback in the comments section to inform design decisions. “It is equal parts art and science,” says Katherine Power, co-founder of Clique Media Group, the publisher behind Who What Wear. “We’re combining our trend forecasting abilities with all of the data we have access to from our audience.”
Fitness and wellbeing platform Lifesum used the data collected via its app to create a health drink packed with the nutrients missing from its customers’ diets. Lifesum’s in-house nutritionist analyzed dietary information from more
than 30,000 London-based users. The results? Londoners were failing to obtain sufficient quantities of key nutrients, including vitamin E, zinc, niacin, pantothenic acid, folate, thiamine and omega 3. After combining this data with people’s behavioral patterns Lifesum developed a juice made from coconut water, kale, spinach, apple, kiwi fruit, pineapple, pear, and omega 3 oil to address their customers’ nutrient deficiency in a smart and simple way.
United Colors of Benetton used an algorithm to create the faces of its latest advertising campaign, digitally rendering six models from statistical data about the ethnic diversity of six cities. Drawing on demographic data from the cities, which included Tokyo, Berlin and New York, its algorithm was able to generate faces that reflect each city’s ethnicity through features including skin tone, hair type and the overall shape of the face.
Similarly, fashion marketplace Lyst used search data to create a series of posters as part of its first advertising campaign, which drew on the vast intelligence the brand holds on its consumers’ buying habits. The tongue-in-cheek campaign features tag lines such as Get a Wax, based on data that searches for “wax” and “high-shine jackets” increased by 114% in New York. So, what’s the value to brands for using data to inform design decisions? It removes the ambiguity of design choices being justified by personal opinion. “Short of purely aesthetic design decisions, having data to back up design choices ensures the best design is what is eventually built,” says Mathias Vagni, lead designer at Lyst. “It removes the ambiguity.”
1. Good data is great; the right data is better. “Value comes from analyzing new data types in the context of specific business knowledge, such as transaction log (T-log) and loyalty information, campaign results, and pricing actions,” according to Howe. “Every shopper engagement, inventory movement, and promotion leaves a data trail providing opportunities for new
capabilities, both from historical data and real-time information, to support decisions across the business.”
2. Trust the data. If the metrics are reliable, brands must be willing to commit to applying the information they’ve uncovered to inform their decision-making.
3. Use data wisely. Data-gathering and analysis can uncover new areas of opportunity, and then suggest the product
with which to key into a consumer need. Lifesum elegantly demonstrated this strategy by delving into data on its consumers’ nutritional habits, and launching a drink to plug the gaps.
4. Solicit feedback. Consumers are on social platforms making their voices heard, so integrate social feedback into the development stage of your range. A screenshot survey is another relatively easy way to enable your consumers to become
co-creators. Using Snapchat you can gather data without taking up much of your customers’ time or energy.