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How Data Influences Customer’s V-Day Shopping

Valentine’s Day might not compare to the December holidays for retailers. But it’s still a massive opportunity. In fact, V-Day is the fourth largest holiday in terms of consumer spending, and sales have continued to rise in recent years. In 2016, total U.S. spending is projected to reach $19.7 billion, according to the National Retail Federation, with customers spending an average of about $150. That’s up from $18.9 billion in 2015. What’s more, Valentine’s Day offers an interesting look at the convergence of commerce in data. Why? For one, it’s a special occasion holiday, like Mother’s Day, the Super Bowl or Halloween. That means marketers have a short window to boost sales and convert customers who shop all the way until the deadline (especially men). Plus, sales are focused on a particular set of items – i.e. flowers, cards, jewelry, apparel and sweets – which enables precise messaging to specific audience segments. But how exactly is data transforming marketing around Valentine’s Day and other special occasions? Data-driven marketing around holidays has the greatest potential to influence sales in three areas: Audience segmenting, message personalization and product demand forecasting. You can find examples all over the web. Here are a few that might not be V-Day specific, but that can easily be adapted to help boost sales around Valentine’s and other special occasions.

Big Data: A Game Changer In The Retail Sector via Forbes

Big Data: A Game Changer In The Retail Sector via Forbes

Wouldn’t it be nice to know what products will be in-demand, the perfect price to sell them at, and which customers will be most interested in them? With Big Data, that’s becoming more and more of a reality. Author Bernard Marr highlights some of the interesting ways Big Data is transforming retail. For example, data helped Russian retailers discover that book sales spike when the weather gets colder. One online retailer’s solution: Increasing book recommendations in their customers’ feeds when temperatures started dropping. Around Valentine’s Day, this type of demand forecasting is critical.

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Sell, Don’t Repel: How to Make Sense of the Retargeting Landscape via Marketo

Sell, Don’t Repel: How to Make Sense of the Retargeting Landscape via Marketo

Retargeting customers can have a huge impact on your bottom line. And this post from the Marketo blog explains why. Ninety-six percent of visitors aren’t ready to buy when they visit your site for the first time. How do you bring them back? Effective retargeting. Your data can help you segment your audience more effectively, craft personalized messages and determine the ideal time to send them. Valentine’s Day is a perfect opportunity to retarget.

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The Beginner’s Guide to Email Segmentation & Personalization via ConversionXL

The Beginner’s Guide to Email Segmentation & Personalization via ConversionXL

Email is one of the most powerful tools for retargeting first-time site visitors, past customers, cart abandoners, etc. – especially around a special occasion like Valentine’s Day. Yet, as the author notes, not all email campaigns are created equal. One-size-fits-all email campaigns are DOA. Instead, you must leverage your data to segment your audience – with some useful examples here – and then personalize the messages you send. This may be a “beginner’s guide,” but there’s useful information that will interest even the savviest of marketers.

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Segmented Messages Are Key to Holiday Email Marketing Success via InternetRetailer

Segmented Messages Are Key to Holiday Email Marketing Success via InternetRetailer

Just what kind of difference can segmentation and personalization make? After the December holidays, three retailers shared how email personalization boosted their marketing efforts. For example, Adore Me – a women’s lingerie and sleepwear retailer – examined data from 2014’s holiday season and discovered that around the holidays many of their visitors are once-a-year shoppers. They personalized messages for this segment of their audience, achieving open rates that were 21 percent better compared to other customer segments.

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Big Data In Retail: How To Win With Predictive Analytics via Forbes

Big Data In Retail: How To Win With Predictive Analytics via Forbes

Markdown optimization: It’s extremely relevant around a holiday like Valentine’s Day. At the end-of-the-season, retailers must cut prices to push goods before demand wanes. But when is the best time to mark down prices? Big Data can reveal the answer. Stage Stores, for example, used predictive analytics to optimize markdown strategy. Their data suggested cutting prices earlier was more effective compared to the staff’s preferred markdown times, with an impressive level of accuracy. Compared to actual staff, data predicted the best time for price drops 90 percent of the time.

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