Retailers are coming off a busy season. Adobe Analytics—used by 8 of the top 10 global Internet retailers to understand how customers shop—shows a final tally of $142.5 billion spent online from November to December, growing 13.1%.
On Cyber Monday alone, nearly $10 Billion was spent online. While these figures are impressive, we also see significant growth off-screen.
What was once considered a death knell for some, physical stores are becoming more of an asset.
BOPIS for instance (“buy online, pick-up in store”) has grown 35% YoY. And in a survey of over 1,000 U.S. consumers, 82% of BOPIS users are likely shop for additional items at the store.
Shoppers value the speed and convenience of BOPIS services, along with the cost savings and preventing porch theft.
It is one of a few major trends pushing retailers to better blend the shopping experience across digital and physical—and meet customers where they are most comfortable shopping.
To support this, Adobe is showcasing Customer Journey Analytics for retailers.
For the first time, brands can now bring together disjointed data via Adobe Experience Platform and get a more accurate view of the overall shopper journey from online to offline.
A set of analytics tools will empower retailers to be more creative in how they piece together and understand this data, while AI/ML in Adobe Sensei can help automate heavy analysis and catch insights the human eye may miss.
Consider a brick-and-click retailer: large network of physical stores, with a heavy investment in eCommerce.
This brand has an incredible number of touch points with shoppers; interactions that happen in-store, on the website and via mobile are intertwined with customer support centers and emerging areas of shopping like voice.
These data sets all sit in different systems, creating multiple and disjointed views of how customers engage.
The net result is clunky shopping experiences that are remedied too late, along with duplicative marketing efforts and missed opportunities in areas like BOPIS.
With Customer Journey Analytics, retailers can finally begin to see where the various online and offline worlds intersect—and see where customers took the next step in their shopping journeys.
Instead of the online team having one perspective and the in-store team having a completely different one, the brand can begin to see the series of actions that occur after shoppers have visited the website, for example.
These kinds of insights are invaluable for many retailers and has long been a missing link in retail analytics.
As an example, brands can begin to understand (at an aggregated, anonymized level) how users conducted product research online, the actions that took place on the website and what drove eventual purchase in-store.
With Analysis Workspace on the Adobe Experience Platform, we took a cue from Photoshop to help brands layer these types of insights on each other and uncover new perspectives on the shopper journey.
The brand can begin to see paths that led to conversion on another channel, or where shoppers are hitting roadblocks.
They can then leverage these insights to improve the overall experience or create new ones.
In the case of The Home Depot and Sprint (Adobe Analytics customers), the early traction they saw in BOPIS pushed them to accelerate these offerings.
Customer Journey Analytics also supports retailers in driving better marketing campaigns.
Subpar marketing experiences can generally be traced back to disjointed data.
One scenario (that many can relate to) is where a customer buys a particular pair of shoes, only to be targeted by ads the next day for the very same pair of shoes.
With a more comprehensive view of the customer, retailers can connect the dots and drive better returns with their marketing investments—while also prevent annoying their customers.
Having a better grasp on customer journeys also can promote better personalization across marketing channels.
Another area that Customer Journey Analytics can support is marketing attribution.
Despite being a critical exercise for marketers, attribution is often done with blinders on, with too much credit given to the first touch point with a customer and the eventual purchase (“last touch”).
Everything in-between ends up being de-valued. But, with a more accurate view of the customer journey, brands can begin to see where marketing efforts are having the most impact and guide investments accordingly.
What analytics tools do you use to understand your customer’s journey?
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