Black Friday weekend goes digital
Consumer spending across digital channels showed significant year-over-year growth over this year's Thanksgiving weekend.
According to data from ComScore, desktop spending surpassed $1 billion on both Thanksgiving and Black Friday. Consumers sitting at desktop PCs spent a total of $1.1 billion, up 9% from $1.01 billion in 2014. On Black Friday, desktop spending grew 10% to $1.66 billion from $1.5 billion.
And insight from Adobe shows that mobile consumers hardly slacked off during the weekend, either. According to Adobe, total online spending reached $2.74 billion on Black Friday and $1.73 billion on Thanksgiving, for a total of $4.47 billion, up 18% from 2014.
Thirty-three percent, or $1.47 billion, of that amount came from mobile devices. Mobile devices accounted for 27% of digital spend on Thanksgiving and Black Friday in 2014. Mobile spending on Black Friday reached $905 million, with $670 million or 74% coming from iPhones and iPads.
Looking at social buzz, Adobe recorded 25% more social media buzz than last year with nearly 4 million mentions. Amazon came out on top with more than 500,000 social media mentions, more than double Target and Walmart combined. Gap, which offered active customer service activity on Twitter, saw the largest increase in social buzz for retailers with 250% year-over-year growth.
Analysis of online Black Friday shopping patterns from the IBM Watson business intelligence platform shows that online sales rose 21% from Black Friday 2014. However, consumers took advantage of deep discounts as average combined desktop and mobile order value for Black Friday was $127.84, down slightly from $129.37 the prior year.
IBM Watson analysis also shows mobile traffic exceeded desktop traffic, accounting for 57% of all online traffic, an increase of 15% from 2014. Mobile sales were also strong, with 36% of all online sales coming from mobile devices, an increase of nearly 30% from the previous year.
For the first time, tablet average order value ($136.42) exceeded that of desktops, which totaled $134.06. Smartphone shoppers spent $121.06 per order, an increase of 4% from 2014. Smartphones accounted for 45% of all online traffic, more than triple the share of tablets (12%). Smartphones also surpassed tablets in sales, driving 21% of online sales (up nearly 75% from 2014), compared to 15.5% driven by tablets.
While desktop spending still outpaces mobile spending, consumers are clearly taking advantage of constant mobile connectivity to browse and research products before making online purchases. In addition, strong growth in mobile purchase volume shows that it is a matter of if, not when, mobile becomes a more important online sales channel than desktop.
And considering the recent spate of social shopping platforms that have been introduced, retailers should closely monitor the growth in Thanksgiving/Black Friday-related social media mentions.
Retailers: Find the Marketing Payoff in Your Data
In a field rich with potential customer data, retail marketers are feeling more data-wealthy than ever as data big and small seem to rule the world. Meanwhile, though, the promise of all this data has lured more than one retailer into a frustrating marketing technology maze that didn’t pay off as planned, sending them in too many directions for too long to cost-efficiently find the customer magic they were promised.
Now is an important time for retail marketers to balance their awe of big data with the practicality of achieving measurable business goals that don’t break the bank.
Technology exists now that allows data to be processed and analyzed at speeds barely imaginable just a few years ago. And it wasn’t long ago that businesses looking to get smart about customer data were forced to invest heavily in technology and resources. Now, marketers can use technology to analyze and understand their customer data in a way that does not rely on expensive infrastructure and systems.
The lure of the 360 degree customer view is hard to resist. But, too many marketers find themselves swimming in a flood of data to reach this dream, losing sight of why they want that 360 degree view of the customer in the first place.
Marketing exists to drive more sales. Companies throw time, money and staff at the dream of this complete view of their customers and often spend more time building systems than executing well thought out, data-driven campaigns.
Big data offers big opportunity, but some big problems, too. It won’t fit on a single server and likely comes from outside your business transactions. And, it will be in an unstructured format, such as customers’ social media comments.
The foundation of any data-driven marketing strategy should be a deep understanding of your current customers. Devoting attention and resources to examining and discovering the value locked into their behavior is often the fastest, most cost-effective route to ROI.
What’s the smartest way to dig in?
The best predictor of the customer of the future is the customer of the past – if we can identify the attributes of the best past customers, we can use them to predict the best future customers…
So, before signing up for a major plunge into your data in search of magical, undiscovered rewards, ask yourself if you can identify your best customers. If not, get started. Pick a metric, define it, and let the data lead you.
Then use a combination of recency and frequency, plus sales information to identify those best customers. Depending on the circumstances, you may also use another measure like lifetime value. Rank your best customers and understand how these customers drive your business.
The 80/20 rule usually holds – 20% of your customers will drive 80% of your business. And that’s where you really dig in to start replicating your most profitable sources. Once identified, use these customers to find your best prospects across all channels.
Get a good look at attributes and behavior in terms of the metrics you’ve set. Develop a deep understanding of customer attributes such as distance-to-stores, income, urbanicity, interests, etc., and both offline and online behavior. Combining knowledge of both attributes and behavior will lead to powerfully predictive models of your best prospects.
Now, you can start your marketing already knowing you have the best prospects targeted. Then measure everything to keep sharpening your focus. Begin the usual test-and-learn cycle with this supercharged starting set and you will be getting a jumpstart on your competitors while reaching your objectives for a better marketing payoff.
Marshall Gibbs is the chief operating officer of Target Data, which combines a marketing optimization platform with data-driven campaign execution to let businesses identify, attract and keep their highest value customers.
Three Trends Impacting Retail Tech Outsourcing in 2016
Information technology outsourcing (ITO), or the strategic hosting and management of technology solutions, services and personnel by a third-party provider, is a popular way for retailers to quickly increase their technological capabilities, and also lower their IT-related capital expenditure.
Jeff Seabloom, managing director at Dallas-based global advisory firm Alsbridge Inc., spoke with Chain Store Age about three trends he sees having a major impact on retail ITO in 2016.
1. Robotic process automation: There may be no other industry more ready and begging for automation than retail, according to Seabloom.
“Automation has an impact on security, supply chain, forecasting and customer-centricity,” he said. “One major area where automation is being applied is in managing IT infrastructure and operations. All of the nastiness of cost management, timelines to market and fast growth market requirements are becoming automated.”
2. Data analytics: The aspeed and intelligence behind data management techniques and capabilities will be hugely disruptive.
“By combining automation and big data/analytics, retailers can understand buying patterns and trends, and be more consumer-centric through more effective loyalty programs, direct marketing campaigns, savings and coupon campaigns and merchandising campaigns,” Seabloom said.
3. Mobility: Add mobility to the mix, and all this results in the ability to deliver a burger to someone who wants it now, or to find the right pair of pants for someone who hates to shop for clothes.
“Imagine the store ‘knowing’ who you are and your buying patterns, and creating a market basket for you to consider based on price, size, style color,” Seabloom added. “Best of all, it knows all this the minute you drive into the lot. How great would that be for the holiday season?”