Dear Retail community,
There are requirements in Retail Omni-Channel Commerce that are obvious, e.g.
· a consistent pricing and promotion management across all channels, including the POS (which is still the dominant channel for most retailers)
· a comprehensive order management, with accurate but performant Available-to-Sell stock determination, dynamic sourcing and product reservation
· a personalized customer experience, consistent across all channel, providing context-relevant information where and when needed.
While the first two are based on tangible data and defined rules, a personalized customer experience is more subtle and complex to provide.
It does not only comprise obvious facts like high quality items at good prices, reliable shipping, great customer service and an accommodating return policy, but also affects a customer’s feelings and emotions, which eventually result in his (subconscious) awareness of your brand.
So you need to keep a personal connection up and running, which is a highly dynamical process, a “journey”, with a lot of ways to kill the delicate flower of customer loyalty.
One of the worst herbicides is SPAM.
Since Henry Ford’s famous quote “I know at least half of my advertising budget works – I just don’t know which half ”, targeted marketing turned out worse year by year. Today we even celebrate, when the global SPAM email rate fell below 50%, the first time in 12 years!
Besides the common email bombardment, even marketing offers without any intentions of misuse are often perceived as SPAM. Why? Because they do not contain content that is personalized and/or contextually relevant to a customer’s current interests and needs.
But how to address it?
How to succeed in this Game of Mass Distraction?
How to predict and provide compelling and contextually relevant recommendations and offers, where and when customers are perceptive for it?
It is simple!
Nowadays it is easier than ever before in human history, to listen and learn what customers are talking, caring, seeking, dreaming and desiring about:
Collect Digital Commerce based customer activities
First of all there are plenty of options to observe, listen and learn more about your customers in your own digital shopping systems, to track and collect their activities and likes, e.g.
- Shopping activities, order history, returns, wish lists, favorites …
- Financial and payment information
- Customer master data
- Feedback and comments on products and service
- Clickstream data
With that knowledge you have a very good data basis for personalized marketing purposes. SAP hybris Marketing based on HANA now enables you to derive and continuously optimize the customer marketing profiles, to slice and dice customers into target groups, to extrapolate analyze and predict interests, enabling you to eventually provide personalized product recommendations in real-time based on the collected customer data.
This is quite an achievement, considering the real-time predictive computing power that wasn’t available or at least any affordable just a few years ago.
But from HBO’s famous “Game of Thrones” TV series we have learned that “nothing someone says before the word ‘BUT’ really counts”, right?
- The big data power and predictive analytics technique used is cutting edge, no questions asked.
- The customer activities collected above are comprehensive, certainly, – everything you can track in your systems, …
You still see the customer from YOUR retailer perspective, not from the customer’s! Bad but common mistake in this new era, where customers are in control and easily switch from one merchant to another.
Whether you like this trend or not, as a retailer you have to adapt, ASAP.
The fat times are NOT over – on the contrary: Technology can give you the leap of advantage to outrun your competition and win in this “Game of Trade”.
But: you have to address customers from THEIR perspective and meet THEIR expectations, not (primarily) yours!
So what can be done to compete and win against the Amazon’s and the eBay’s on this world?
Here’s a proposal:
Collect Brick & Mortar Store based customer activities
Leverage your strength: your store business, still by far the biggest commerce channel in Retail. Customers leave valuable information even in stores which you can easily leverage and factor in as another, so far missing puzzle piece of the 360 degrees customer view.
I don’t only mean analyzing millions of POS data linked to a certain customer via their loyalty card. This is a low brainer and should be included without saying in the customer marketing profile repository of the hybris Marketing Data Management component.
Customers behave different in local stores than in the digital commerce. You can use this insight to your advantage, e.g. when you offer click & collect across channels.
Go beyond that and use modern technology to collect customer interactions beyond POS: Track the customer’s movement in your store: which aisles they use, where they stop, and what they buy at the end. You can capture this information by shopping trolleys equipped with beacon technology, as some retailers already do. Mapping with the customer number is done via the loyalty card at the POS. Of course local legal requirements are to be followed.
Click and collect, pick up in store, online wish list items bought locally, price sensitivity, quality standards per segment or product group, their affinity to promotions and discount levels, paper coupons and online coupons, loyalty programs, preferred payment methods, smartphone based payments …
Learn as much as you can from customer store activities and behavior. All this information are collected in the SAP Customer Activity Repository and are available as HANA content for customer segmentation and context relevant personalization.
More to collect
Beyond the pure commerce/sales, include also
- your marketing campaigns (online/TV/social media,…), local print advertisements, …
- bonus programs
- media campaigns of your vendors
- … and whatever you run in this regard …
to analyze the customer response to advertisements and campaigns.
Collect external data
OK, now you are collecting literally all the data you can get from your own company ecosystem.
Let’s go beyond pure commerce related data. And let’s go bold!
- Factor in market research and environmental data:
- external market research data from companies like AC Nielsen, IRI etc.
- geospatial data, like income structure, education level, distance to next store, rural/city/mountain area, traffic, …
- local weather data and forecast, to predict buying behavior on sunny/rainy/snowy weekends and workdays, and link it to
- calendar data like holiday periods, bank holidays, start of school years, local events …
Enough? Come on!
Collect Social Media network based customer activities
Let’s step now into now Social Media networks, where your customers unveil their interests, dreams, wishes and desires. They share content, likes and comments, chat with friends and peers, …. – and you can use their traces for your personalized marketing!
But how you could possibly enquire all this data from so many different social media networks? And how to find your customers in this vast universe with billions of users?
- Allow your customers to register on your digital commerce platform, e.g. with their facebook login
- Ask your customers for their social media accounts: Facebook, Twitter, Bing, LinkedIn, Pinterest… accounts. Customers are willing to share private data for convenience, fun and benefits.
- Retrieve social media data from providers like DataSift or others who consolidates billions of social conversations into their platforms
ALL that is quite an amount of data, requiring hardware, big data memory, CPU power, maybe even HADOOP clusters connected, resources, budget, time …
No need to collect and enquire all data and all at once. Rome wasn’t built in one day.
Focus on marketing relevant data first. Hang and swing from one data source to the next. Customers have a lifecycle, and you can track and analyze their journey, and predict the road ahead. It’s a continuous process.
How to use this data?
How to PREDICT a customer’s need and interest in a personalized and contextual fashion??
Now you have the most comprehensive collection of customer activities from all angles you can legally get, and it is getting bigger every millisecond.
But how to import, store, process and analyze this massive amount of structured and unstructured data in a single repository?
Which system is powerful enough to
- analyze all the various data and information, with all their known and unknown relations in between, as a whole
- match merge and enrich with additional information to your likings
- to be able to
- slice and dice customers into target groups
- determine short/mid/long term customer interests
- find patterns and recurrences
- identify preferred payment methods and promotion behavior
and eventually predict customer behavior and interests in a contextual matter, more precisely than ever before?
The answer is simple. The answer is SAP hybris Marketing based on SAP HANA, in future combined with the most comprehensive customer profile across pillars Sales, service, Marketing and Commerce, SAP hybris Profile.
Its immense power of predictive analytics you can use today to support all your direct marketing activities in web, social, commerce, email, print – virtually in every customer touch point across your channels.
The SAP HANA based application is specifically designed for the immense in-memory computing power you need to analyze the customer marketing activities and interactions, bring the data into the actual context, assign customers to target groups on the fly, and predict and provide personalized product recommendations in a contextual manner in real-time.
The SAP HANA data management platform will allow you to handle all the different types of data which come in at high volume, velocity, variety, variability and veracity (see Wikipedia on big data characteristic).
Therefore it comes to no surprise that SAP hybris Marketing is a key component of the SAP Retail Omni-Channel Commerce reference scenario, ideally combined and co-deployed on the same SAP HANA instance along with SAP Customer Activity Repository, which brings in omnichannel transactional data and store data. Make use of the RDS for hybris Marketing for Retail, to use CAR based content and attributes within hybris Marketing, e.g. for segmentation.
Customers and partners with S-User can get a glimpse about the 2015/16 Omni-Channel roadmap in the Innovations section of SAP Service Marketplace (use the search term “omnichannel commerce”).
Stay tuned for updates and extensions of this blog, and in the SCN space SAP for Retail.
Dr. Ingo Woesner
Global Director, Outbound Product Management Retail Omni-Channel