Marta Pichlak-Miarka, Business Consultant Customer Intelligence SAS
Customer Web Analytics and online personalization.
When you go to the supermarket you don’t expect the employees to know your name or to rearrange the store space for you. Yet when you visit your “shop around the corner” you appreciate the fact that staff knows who you are, that you have a 3 year old kid and that your favorite cheesecake is ordered just for you every Saturday because you buy it every week. When people shop online they have a similar set of expectations and they will get annoyed that on their third visit to your e-shop you still don’t know that they live in Antwerp and you keep displaying them banners of products they’ve already bought
In this session you will learn:
What is the difference between Site Centric digital measurement and Customer Centric approach and why it’s crucial.
Why real time data is less important than data ready for real time decisioning
How state of the art technologies support next best offers targeting, web site personalization and remarketing
Why you need tools that will support multichannel marketing across online and offline channels
How does this look in practice (demonstration of key capabilities)
When you go to the supermarket you don’t expect the employees to know your name or to rearrange the store space for you. Yet when you visit your “shop around the corner” you appreciate the fact that staff knows who you are, that you have a 3 year old kid and that your favorite cheesecake is ordered just for you every Saturday because you buy it every week
My shop around the corener… When people shop online they have a similar set of expectations and they will get annoyed that on their third visit to your e-shop you still don’t know that they live in Antwerp and you keep displaying them banners of products they’ve already bought
My personal example. I was surprised how well endless- a shoe online store ( part of Amazon) used my purchase information in their next best offers. After the purchase I was encouraged to make a product review of the shoes that I bought. I posted a review saying how much I loved my new Guess shoes. I browsed the endless web site for bags but didn’t buy anything. Endless has already identified by a Nine West fan and notifies me whenever there are new arrivals from this brand.
One month later I received a newsletter with various offers but this red bag that was a perfect fit for my shoes was featured as the first one. I clicked the e-mail and looked at the product ( I didn’t buyit though because of the price, yet it was still a relevant communication. Since I’m a new endless customer they have to collect more information and transactional data to show me products in my price range;-) SAS and Amazon Much as Amazon is not using SAS in managing their e-mail campaigns they use SAS for analytics and testing algorithms. Amazon.com uses SAS to test the effectiveness of a variety of features, designs and technologies and to measure how well they served the customer. “While we don’t use SAS for the operational implementation of these features, we count on SAS to enable our test-and-learn approach for evaluating new product page layouts and new search technology Amazon uses SAS to analyze operational and financial data to determine the impact that test algorithms have on the customer experience
Many companies have lost the shop around the corner opportunity because their customers move online. Think about PC banking …50% of the customers of one of the biggest belgian banks are online Online retail is another example Many of our customers today take a strategic decisions about becoming customer centric Some of them don’t know if they can become customer centric as it’s easier said than done.
For the next 20 minutes I’m going to take you through 6 challenges that most companies/our customers face to restore the shop around the corner experience and how does analytics and technology help address these challenges.
A mix between a giraffe and zebra
Did he complete the task Did he find what he was looking for How long did it take the customer to find what he was looking for What products did he view What products did he put in chart
We want that box…It won’t happen overnight
There are a number of ways to get a data into an analytical mart 1) Data feeds from existing tag vendor 2) Log processing 3) Universal Tag ( f.e tagMan) 4) Direct Applications Insert 5) Dedicated Infrastructure – solutions such as CXA Key issues All 1-4 ways have some substantial drwabacks The richness of data is limited, standard web analytics solution will not be able to capture Mouse over, mouse clicks Page loads, content load Navigation events User input and form data/completion Rich media interactions There has to be pre planning of data capture and some cuztomization of what you want to tag The quality of data is poor Solutions such as such Customer Experience Analytics have: Easy single tag deployment Robust data collection Rich out of the box model- data flow directly into warehouse structures so that your analysts can start working with it in a much more productive way, it shortens time to real benefits Data Quality:greater accuracy of client matching and does the matching over a prioritized list of customer attributes. For example – we could match you on Name, Address, Phone and email or any combination of these. So if you used 2 different emails on the site you would be seen as 2 different customers – we would pick that up via your other attributes. Data structures that allow integration with other data sources Data environment that is Ready for further analysis, segmentation etc. Data ready for real time decisioning ad3. One of the most powerful aspect of solutions such as CXA is the fact that they were designed to be a measurement infrastructure for the warehouse. It’s much more than just a data collection. A really good measurement infrastructure is much more than tag governance and the data model is a - perhaps the - critical ingredient. CXA provides a pre-built data-model appropriate to your EDW that is designed to take much of the initial work out of building a digital analytics mart. The pre-planned data structures capture ALL of the event level data and provide several different layers designed to make it easier to distil meaning from the data. Particularly important is the framework for flexible goal definition. Ad6. You have to use your data responsibly and appropriately and respect customer privacy. This means things like offering an opt out for customers who want their details to stay private and providing clear information on how the data is used.
There is more and more real-time data available. Google Analytics is updated, officially, every hour. Then there are cool tools like Chartbeat, etc. My personal perspective on real time analytics is…. if you can’t take real-time action then why do you want real time data? In 99% of the cases real-time data is not actionable On aggregate level it is not statistically significant and you can misinterpret the signals Without customer level data most companies can’t actually take any action even if there is an actionable signal (change campaigns, landing pages, stop emails from going out or whatever).
The most important thing however is not to confuse acting in realtime with recording data in realtime. The really interesting development comes when you act in real time but take the relationship approach . You don’t only look at this visit in isolation but you use tools which can look at the longer term interactions between your brand and the customer.
There is a paradox, everyone in marketing has been going around for years saying online is different yet they keep on doing what they are doing offline blasting off generic message. The key to online is that you can get lots of data on your customers behavior for better targeting of marketing and to dynamically build content around them whem they come to your website. Consumers are going to come to expect it — you can’t just have a simple, one-size-fits-all experience” for all consumers. I think the expectations are increasing. I don’t see people wanting to go back to a less personalized, less social, more irrelevant experience, so I think [the customization] trend is going to continue,”.
Getting the balance wrong between acting in real time and using long term behaviour leads to paradoxically less relevant messages and less optimal decisions. A classic example are services which send discount offers within hours to people who have abandoned shopping carts. These people may have just been disctracted by something else. If you just act in real time on real time visits and ignore long term data you have no idea whether sending money off offers within couple of houres is the right thing to do. You can discount people who whould have bought with you anyway. And above all you don’t train people to abandon carts on purpose… Another example is a book store. Just because I once clicked on the books for Dummies doesn’t mean I will only be intrested in Dummies books. If you don’t take the longer view of my preferences across multiple sessions your recommendations will not be correct
The CSV is a centrally maintained set of all attributes required to make decisions about a customer, and is available in real time at all touch points to ensure relevant interactions
Customers expect consistent experience regardless of the channel- whether they contact your branch, browse the web or contact call center Online has become the most important channel for your customers to look for information. Think about loyalty card and its ability to collect data and support targeted marketing strategies…how much more information can be gathered from the online channel. Loyalty cards only know about what your customers purchased whereas from the online channel you can see what they looked at and searched but did not buy How much powerful is that This data provides your customers intentions and motivations Online is becoming a central channel for collecting signals that should be analyzed and used to trigger marketing activities across channels Online signals should be avialble across touch points
You have to use your data responsibly and appropriately and respect customer privacy. This means things like offering an opt out for customers who want their details to stay private and providing clear information on how the data is used.
Ad 2 don’t confuse collecting data in real time with acting on the data in realtime
Jim Sterne is an international speaker on electronic marketing and customer interaction. A consultant to Fortune 500 companies and entrepreneurs, Sterne focuses his twenty five years in sales and marketing on measuring the value of the Internet as a medium for creating and strengthening customer relationships. Sterne has written seven books on Internet advertising, marketing and customer service including, "Social Media Metrics: How to Measure and Optimize Your Marketing Investment." Sterne is the producer of the international eMetrics Marketing Optimization Summits www.emetrics.org and is the co-founder and current Chairman of the Web Analytics Association www.WebAnalyticsAssociation.org Sterne was named one of the 50 most influential people in digital marketing by Revolution, the United Kingdom's premier interactive marketing magazine and one of the top 25 Hot Speakers by the National Speakers Association.
