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Big Data for Small Brands

Written by Peter Devereaux | Jun 4, 2014 5:00:00 AM

By Amberly Dressler, Managing Editor

Big data isn't just for big brands. Increasingly, small- and mid-size companies are learning how to collect, analyze and leverage large amounts of information for the benefit of their enterprises.

Today, however, big data - a popular term for data that is too large to process with conventional business analytics software - is more accessible and manageable because it's all relative to a company's size and goals. Fittingly, Jerry Jao, the CEO of Retention Science, defines the buzz phrase as "intelligence at scale."

Still, some decision-makers are being convinced, by different vendors according to Jao, that they need access to all the data under the digital sun, leaving them with little information about how actually to scale the data, how to measure it, how to make it useful and how, ultimately, to drive decisions based on it.

The real big data win is when marketers responsible for smaller brands understand what data is most valuable to them and what inexpensive tools are available to help make it actionable.

Mind Blowing Personalization

Discover three examples of using your CRM to leverage big data insights at wsm.co/datacrms Size Doesn't Matter...

To put big data into perspective, it's important to understand that not every business has access to the same information. Commerce sites, for example, often measure visit frequency, average order value (AOV) and items per order to build in-depth customer profiles, as well as to understand general conversion trends. Conversely, an information publisher may analyze how long certain customer types are spending on articles in certain categories, what newsletters are popular with that subscriber group and so on. For example, the information publisher could determine that executive-level professionals spend more time in design and development advice articles than blogs about social media but subscribe most to email marketing newsletters; these are valuable insights for his content development and advertising initiatives. From these business specific datapoints, marketers can see which additional metrics will help them improve their bottom lines.

At its simplest, understanding customers' behaviors and intentions comes down to setting up analytics tracking appropriately. A retailer, for instance, who wants to know where his most valuable customers are coming from, needs to set up ecommerce tracking on his shopping cart to collect data on each transaction.

The information collected can include which product(s) was/were purchased, the channel source, purchase amount, and billing city, state and country. Specifically, tracking ecommerce transactions in Google Analytics would show the ecommerce merchant the high-value locations and referral/campaign sources.

Aside from knowing which channels to invest in (SBOs wouldn't want to repeat what they are doing on Facebook, for example, if it's not bringing conversions), marketers can use this same information to personalize other campaigns, like email. Batch-and-blast email methods are far from extinct, but if marketers were to know, for example, that blogger-referred customers have high AOVs, shouldn't they get a different message than Facebook-referred customers who are buying less/if at all? Yes, because their needs are different. By being thoughtful and providing this type of segmentation (thanks to data), customers will have more customized experiences that many big brands are giving them and even the smallest businesses will have better selling opportunities.

...But Privacy Does

Unsurprisingly, with an increasing amount of data at every company's disposal, privacy is a huge concern for Internet users. The simplest way to quiet customers' fears is to avoid surprises. For example, retailers asking visitors to sign up for email newsletters, should have their easy-to-read disclosures ready, along with a list of what they plan on doing with the addresses (e.g. weekly emails, promotional offers, etc.). This level of transparency, according to Jao, is often acceptable to most consumers.

Despite consumers being skeptical about how brands will use their information, research shows they're still voluntarily providing it to have more personalized digital experiences. Meaning, they are freely filling out profiles (with birthdates, preferences, etc.) in exchange for greater relevancy. That said, small brands shouldn't hesitate to bolster their personalization efforts by leveraging the "big data" that is important to increasing their bottom lines by way of customer experience.