By Rama Ramakrishnan, CEO, CQuotient
The word “omnichannel” might be the most dominant word in retail in 2013. But for all its importance, it is still an emerging concept. Even finding a definition of the word proved challenging, as everyone has their own idea of what omnichannel means. The term, as defined by Wikipedia, means “the evolution of multichannel retailing, but is concentrated more on a seamless approach to the consumer experience through all available shopping channels, i.e. mobile internet devices, computers, bricks-and-mortar, television, radio, direct mail, catalog and so on.”
This concept of omnichannel retailing is the Holy Grail for retail marketing success. But, to fully execute omnichannel, retailers need to know their customers – and I mean actually know them. This deep understanding is challenging but can be incredibly rewarding. The trick is using the treasure trove of customer data that you already have.
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Earlier this year, I introduced retailers to “Jane” and explained how, by using the right combination of big data and predictive analytics, retailers have the power to decipher Jane’s individual behaviors, taste and style based on her online and offline browsing and shopping habits, and tailor email campaigns accordingly. In this article I’ll go beyond email and introduce retailers to “omnichannel Jane.”
Paint The Full Omnichannel Picture
Some retailers think that by blasting out messages across multiple channels they are successfully executing omnichannel marketing. Using multiple channels in one campaign is a start, but the truth is the same person may behave differently from channel-to-channel, and messages should be tailored to those behaviors accordingly. For example, while many consumers read email on their smartphones, they may not actually click through to purchase and prefer to wait until they are physically in a store. The savviest retailers understand this about their shoppers and will find ways to tailor messaging accordingly. Let’s use the example of Jane again; you’ll remember that by using data from multiple touch points, we painted a picture of Jane that looked like this:
Jane’s Product Affinities
- Jane loves the latest fashion (4 of 5 items were fashion items)
- “Tight fit”, “skinny” and “chic” are attributes that appear in 3 of 4 apparel of items she purchased
- 73% of customers who share these characteristics are now buying colored denim and cropped fall jackets
- Jane likes brands like Gucci and Prada
Jane’s Offer And Price Sensitivity
- Full price shopper
- Premium price point in categories
Jane’s Attrition Risk And Momentum
- Opened 3 of last 7 emails over past 10 days, but did not click through
- Approaching observed cadence for shoppers like Jane who buy earlier in a new season
- 62% chance of shopping in next 2 weeks
Jane’s Hole In The Basket Up-sell
- 65% probability of buying a handbag, even though has never before
- 73% chance of repeating a purchase in “Dresses”
We used the data above to craft an email that inspires Jane to act based on her interests. That is certainly effective, but omni-channel can do even better. The additional data may look something like this:
Mobile
- 78% of the time, when Jane opens an email she does so on her smartphone
- Jane has clicked through 0% of mobile communications
- 25% of the time she re-opened the email on lap top or tablet, usually within 12 hours of the mobile open, and she clicked through these emails 25% of the time
- Taken together, almost 5% of the emails she opened on mobile were ultimately clicked through on some device
Tablet
- 50% of her browse sessions in the last 3 months were via tablet, the rest were via a PC
- All browse sessions were after 10 PM EST
- The sessions lasted an average of 7 minutes, and she looked at 5-8 product pages each time
- Jane added one item to her cart
In-store
- Jane made 2 purchases in the past 2 months, both were preceded by a site browse session in the 6 days prior
- No coupons were used
- One basked included an item she had previously added to her ecommerce shopping cart, plus 2 other related items from other departments
- One basket contained an item with the same brand and category she had browsed online prior to her store visit
Looking at this detailed picture of Jane, we can predict that Jane is very tech savvy and is actively engaged with the retailer digitally, but prefers to shop in-store.
This insight is not only interesting but also actionable. For example, most retailers have an automated “abandoned shopping cart” email program. Essentially, they automatically email someone who left something in their cart with a reminder to complete the purchase. They may also include an incentive like free shipping or 10% off. These tend to work, but it is NOT the right campaign for Jane. Instead the retailer should send Jane an email informing her the item is in stock in her local store (along with related items), offer a way to reserve it at the store for 24 hours, and provide a “spend get” in-store coupon that is $20 more than the item’s price to encourage her to expand her shopping once she goes there. This is both a win for the retailer (larger order size) and a win for Jane as she gets valuable information (what she likes is in store now), a great service (“we’ll hold it for you”) and a chance to save money (“Save 10% if spend more than $150”).
Measure Holistically
This brings me to my next point and the biggest mistake I see retailers making today – measurement. While behaviors differ by channel and messages should be tailored individually, the full omnichannel picture must be considered when measuring success. After all, there is still only one Jane acting all these channels – not different “Janes” per channel. Your goal is to increase your share of her wallet so you have to look at her behavior in total to judge success. Too often, however, retailers are siloed by channel and so are their success metrics. An email team that worked to personalize a communication to Jane on her smartphone may consider that communication a failure because Jane did not click through, when in fact seeing that message inspired Jane to go and purchase that very item in-store. For many retailers, sales across channels are a political hot potato ands they are not willing to confront it. That is their loss and they will end up making incorrect investment decisions because of it. Retailers that intend on being truly Omnichannel, however, know they must measure ROI across channels and become channel agnostic. A sale is a sale is a sale. That is how customers see it, and so must retailers.
Achieving Omnichannel During The Holidays And Into 2014
Achieving the omnichannel Holy Grail is not just about the data retailers are collecting, but how they are translating that data into actionable insights. Many technology vendors collect data on consumers for retailers, but collecting the data is only the start. If you can’t do something with that data, then you haven’t moved the needle for your business or improved the experience for your customer.
Omnichannel, while a popular buzzword, has yet to be successfully executed, leaving a lot of opportunity out there for retailers to use true omnichannel personalization as a way to pull away from the pack and rise above the competition.
Rama Ramakrishnan is CEO & Founder of CQuotient. Ramakrishnan is an analytics entrepreneur with more than 20 years of experience in applying analytics to business problems across a range of industries. He founded CQuotient to transform retailer economics by infusing customer insight systematically into their everyday decisions. Prior to CQuotient, Ramakrishnan taught analytics in the MBA program at MIT Sloan School of Management. Earlier in his career, as chief scientist and VP of R&D at price optimization software firm ProfitLogic, Ramakrishnan pioneered the development of techniques for optimally pricing and promoting seasonal and fashion-sensitive merchandise for retailers.
