Econsultancy: How fashion brands are setting trends in digital

How can fashion retailers use dynamic data to meet consumer expectations and take advantage of new channels?

It was once believed that people just wouldn’t buy clothes online; that fashion consumers needed to touch and try what they would be wearing – but this is clearly not the case, as online sales grow and brands continue to innovate.

Online fashion sales grew by 185% between 2007 and 2012, and sales are predicted to rise by 41% by 2017.

Read more

Marketing & Com – Lancôme innove en matière d’expérience client grâce au digital

Lancôme, leader mondial du secteur des produits de beauté, propose une personnalisation en ligne ses clients. La marque innove par la possibilité de construction complète et sur-mesure de son look, à partir de ses produits cosmétiques.

Lancôme s’est associée à RichRelevance pour élaborer cette innovation digitale. Ainsi chaque client peut utiliser les produits cosmétiques Lancôme pour personnaliser son look, selon ses préférences et l’expertise de la marque. Le site propose ainsi des produits en fonction du teint du client, et d’assortiments réalisés par ces experts.

Read more

Chain Store Age – Barneys gets closer to the customer

New York – For the upscale, 33-store Barneys New York, customer experience is everything. Affluent shoppers buying high-priced merchandise have certain expectations beyond the availability of quality items, regardless of channel they choose.

“We want every customer to have an online experience personalized to their taste profile, preference and geography, just as we would do in our flagship stores,” Matthew Woolsey, executive VP of Barneys digital, told Chain Store Age.

Read more

Retail Gazette – LFW: project technology

“Gone are the days where stores are the forefront of the marketing stage and mobile devices are used predominantly for text messages and playing snake”, says Matthieu Chouard at RichRelevance, an omnichannel personalisation specialist. This couldn’t more true than at this season’s ‘Fashion Month’, where technology dominated the catwalk.

Read more

Information Age – What the retail sector can learn from London Fashion Week's tech innovation

This season’s London Fashion Week showcased some flamboyant fashion- and equally dazzling examples of omnichannel, personalised digital marketing strategies.
Every season, the illustrious London Fashion Week gets more high tech as retailers seek to make the show an interactive, omnichannel brand experience.

Read more

Try This On for Size: Five Best Practices for Apparel Personalization

So, you just started as a Sr. Product Manager at an online apparel retailer and “personalization” falls squarely in your lap. Product recommendations are already implemented on the site and are doing reasonably well—but, being the over-achiever that you are, you’ve promised your boss an additional 2% revenue per session lift in the next quarter, and are now scratching your head wondering just how to accomplish that feat. Don’t worry—we’re here to help.

First off, it’s important to understand that personalization isn’t one-size-fits-all. Consumers shop differently across verticals; what elicits conversion in electronics or consumer packaged goods is vastly different from what drives incremental revenue in apparel. With the former, shoppers primarily buy based on features and capabilities. In apparel, inspiration and aesthetic compel shoppers to buy. A shopper envisions herself wearing a jacket, incorporating it into her wardrobe, and a compulsion to buy is born. Fundamentally, apparel retailers must deliver a different set of experiences to drive the buy decision and maximize incremental revenue.

With that in mind, you can meet your goal and impress your boss with these 5 apparel best practices—which you can execute and validate within the next 90 days:

1. Remove price from email recommendations. Unless your pricing strategy is to appeal to bargain buyers, do not display price in email recommendations. Price can deter clicks by introducing another dimension with which to evaluate a product. With price exposed upfront, the customer must make a decision as to whether she can afford the item. Remove the price and you mitigate customer objection—particularly on high-ticket items. Instead, dazzle the shopper with product imagery and let them view price once they click through to the site—where they’ll have the opportunity to absorb other salient information that communicates value and endorses the offer. We’ve observed up to a 40% increase in click-through rates after removing prices in apparel email recommendations.

2. Recommend higher priced alternatives on the item page. Influence AOV to drive up per-session revenue. You may take a hit on conversion, but the increase in order values makes this a winning proposition. Start by testing the status quo (the control) against boosting the display frequency of similar items priced at least 85% the price of the product on the page. Or, to improve your chances of identifying the proper threshold, conduct a four-way test, adding treatments that boost items priced greater than 90% and 95% the price of the seed, respectively. It’s important to boost rather than only recommend these items as the latter can result in no products being available for display.

3. Strategically place recommendations to keep external search traffic onsite. You spend a lot of money on SEO and SEM, but you’re still seeing high bounce rates from traffic arriving on item pages from external search. Rather than hoping that the lone merchandised product will resonate with the shopper, provide more relevant opportunities to engage with your catalog. To achieve this, display recommendations for similar items across the top of the page, only when the shopper lands from external search. Across a number of sites, we have been able to reduce bounce rates for external search traffic—landing on the items page—from 5%-20%.

4. Apply user segmentation to recommendations. More than most verticals, preferences of apparel shoppers vary widely based on geo-location, wealth, gender and other identifiers. Whereas a shopper in Minneapolis might be cross-sold a fashionable coat for a pair of pumps, a shopper in Miami might find a light sweater more suitable. “People who bought this item also bought” should then effectively be “People [in Florida] who bought this item also bought.” If you segment your customer base, instead of using aggregate shopping behavior to inform personalization, it’s best to leverage these segments in product, content and promotion-based recommendations. By modeling recommendations off of sub-communities to which customers belong, you deliver greater relevance throughout the shopping experience.

5. Personalize your category list pages. Category list pages—as many exist today—offer very little in the way of personalization. They’re oftentimes a long matrix of products that can be sorted by price, popularity or newness—meaning the number of page versions equals the number of sort dimensions. Clearly, this doesn’t reflect the diverse interests of your shopper base. Demonstrate that you understand the shopper’s preferences by personalizing the product sort order on these pages based upon her historical behavior. If she has an affinity toward a specific brand or newness, proactively rank the results accordingly and accelerate discovery of the right products. Layering personalization on these list pages can increase the per-session revenue of shoppers exposed to these pages by up to 2.5%.

So, there you have it—five optimizations to land you a 2% increase in online revenue and make you a rock star within your organization. If you would like to learn more about these best practices, you can view this 20-minute webinar. For additional questions on implementing these best practices, please contact your Account Manager or email

More posts