Fuel your retail multi-channel strategy with advanced analytics
Customers have welcomed the concept of multichannel retail with open arms – the fact that nearly 50% of customers today are multi-channel purchasers tells us this. Why should retailers take note? Because the ones who’ve been successful in this space understand a couple of crucial aspects such as how their customers want to shop with them, and consistently take advantage of the opportunity of being able to present a single view of their brand, regardless of which touch point the customer is using to interact with them. Multi-channel retail also gives retailers more opportunities to present their products in front of customers whom they wouldn’t have been able to reach with a single channel.
The most important aspect of multi-channel retail, however, is that it is the gate-way to the concept of omni-channel retail. So what exactly is the difference between multi-channel and omni-channel? Like we mentioned above, multi-channel means that your brand is present across key channels like brick-and-mortar stores, social media & mobile and still making sure that your brand can reach potential and existing customers on every channel does take a considerable amount of time, money and energy. Omni-channel retail takes this infrastructure to the next level: it links activities among offline shopping and the many digital channels so that a customer can begin an engagement on one channel and conclude the transaction on another. This is especially critical as shoppers are increasingly using a number of channels to complete their transactions, as a recent survey of US online shoppers done by PriceGrabber reveals, 45% of respondents said that they were choosing to combine online, brick-and-mortar and mobile shopping while just 12% said they shopped only in brick-and-mortar shops.
So with multichannel customers having a potential to spend an average 4-5 times more than other customers, what aspects of transaction and customer information should retailers track, and how should they use that information while making decisions related to strategies and tactics?
Use analytics to trace shoppers’ footprints – online and offline
Macy’s keeps track of customer browsing data by recording their browsing history while they surf the Macy’s website. The retailer then uses this browsing history to target e-mail offers. According to Peter Sachse, Macy’s CMO, “There are times we’ll send out 18 million unique emails… down to the point of emailing a shopper with a message like… We just saw you last night on the women’s shoes part of the website, and then send that shopper a targeted shoe promotion.” They can now do the same by looking at location data from mobile devices as the retailer can also use this same information in a case where the customer was present in a store but didn’t make a transaction – mailing a coupon for an offer in the shoe category would be effective. Other possible scenarios include sending customers while they are in the store (provided they have opted-in for the service). The retailer is also working to create “dynamic customer experiences” and Sachse says the retailer intends to customize the content on the home page “based on everything we know about you [the customer]“.
Use analytics to make the multi-channel marketing connect
Bass Pro is a retailer of hunting, fishing, camping and related outdoor recreation merchandise. Like most marketing divisions in retail organizations, theirs too struggled to determine the effect of the printed catalogs they mailed out on the brick-and-mortar and online sales. So how did they use analytics in a situation like this to get a better understanding of their multi-channel customers? The retailer tracked which customers brought their catalogs in to Bass Pro stores or placed orders on Bass Pro’s Website after having received the print book. As it captures telephone numbers with most of its store transactions, it reverse-appends them to names and addresses every night. The $325 million-plus marketer then adjusted circulation for subsequent mailings so that they can send catalogs to customers who used them to make purchases through other channels. Bass Pro also found that of its fall/holiday retail and Web sales, almost 34% had some connection to its catalog mailings.
Bass Pro also ensures that it consolidates the databases that marketers keep for each marketing channel into one central depository. This makes it easier for marketers to find retail or online buyers who have been influenced by the catalog, so that they can spend precious time and money on critical customers.
Use analytics to establish integrated customer identity
Another retailer who leverages this stored customer information and uses it across channels to establish customer identity is multi-channel flower and gift retailer
1-800-flowers.com. The retailer uses an integrated customer data warehouse for all its brands and channels, and literally keeps track of every customer’s ‘path to purchase’ – for all interactions across all channels. Not only this, the company also identifies a preferred channel for each type of interaction with each customer. The retailer handles the tracking of customer reaction to offline promotions with coupon codes tied to the offline channel, but it also calls repeat customers ahead of anniversaries, birthdays and other occasions related to their loved ones and offer phone-only prices and discounts.
Use analytics to cross-sell across multiple channels
Retailers who effectively review insight from their analytics systems also spot opportunities to cross-sell other products. For example, when electronics retailer Best Buy analyzed customer data of shoppers who bought iPods, the retailer identified that customers tended to return in about two weeks to purchase accessories. The company took advantage of these insights and began to include literature about accessories with the iPod – but more importantly, it sends out timely emails to buyers about available accessories to give them that little extra push.
Retail analytics: giving your multi-channel strategy direction
An efficient retail analytics system that’s able to track customer preferences in terms of products and channels is a critical requirement for multi-channel, cross-channel and omni-channel retailers. It’s essential for such a retail analytics system to be able to store multi-channel analytics collected in a customer data warehouse, so that it can capture and record activity across channels. Retailers can then create behavioral targeting models according to channel preferences, cross-sell the right products at the right time and customize offers.
Is your retail analytics system capable of collecting this vast variety of data across retail channels?
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