5 tips to personalize digital customer experiences

At the online “flash sale” retailer Gilt, success comes from breaking through the clutter, and from ensuring that their offers matter in the grand scheme of their customers' lives. And with more than 8 million "members" (potential customers), they've managed to create a culture where customers are the company’s biggest advocates and evangelists.

So how are they doing it? They are operating in a market where consumers are more informed and empowered than ever. And it's not uncommon for customers nowadays to reference a half-dozen or more sources to make a purchase decision. One thing's for sure - they're not backing away from the fray. In fact, they create their own fray - several times a day. Every. Single. Day.

Gilt has elevated online shopping to a competitive sport by:

  • Starting with a coveted set of products, hand-picked to entice – luxury goods for women, men, kids and home.
  • Sourcing them directly from more than 6,000 partner brands, as well as unique local experiences.
  • Offering them in limited quantities, discounted up to 60 percent – but only to an exclusive audience and only for a limited time.
  • Tamara Gruzbarg is Senior Director of Analytics and Research at Gilt.

    Tamara Gruzbarg

    Starting new sales at a designated time each day – more than 200 sales a week.

Their approach to applying marketing analytics to customer data and processes is at the heart of how they can operate so nimbly, and personalize the digital customer experience for so many people.

This repeated success and the story behind it have been captured in a webinar conclusions paper that includes 5 tips from Tamara Gruzbarg, Gilt's Senior Director of Analytics and Research, on how to use analytics to personalize digital customer experiences:

  1. Know your data sources. Marketers have many more data sources available now than we could have ever imagined. Before you start developing specific analytical tools, it’s important to understand how those various data sources can be used and how to optimize the predictive value of the data.
  2. Focus on quick wins. There’s no need to wait until you have all the most perfect data and analytical tools available to you. A lot of what is now built out at Gilt started as an experiment four or five years ago. Initial insights can be incorporated into future comprehensive strategies.”
  3. Test and measure. You should always expect questions about incremental gains, or how a particular initiative moved the needle. So it is important to have appropriate test designs for all of your analytics initiatives, for accurate and meaningful measurement of results.
  4. Continue to monitor, refine and optimize. Our work is never done. Even when we have developed something that we think is optimal at this point, our customers and market environment are always changing over time, which requires us to be dynamic and agile.
  5. Start somewhere, but start now. Even if you’re not in a position to think about a holistic and sophisticated loyalty program, there are always things you can do improve the customer experience and start that cycle of loyalty. Never be afraid to start.

To get the whole story, download the conclusions paper, Build Loyalty with a Personalized Digital Experience. Let me know what you think!

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Three steps to improve your digital marketing

digital_baseballLast weekend, I took my nine-year-old son to a batting cage to get ready for his upcoming baseball season. He's a natural athlete, but soccer has been his full-time sport of choice for the last two years, so he needed some reps swinging the bat to switch gears to baseball.

As he stepped into the cage, I stood on the outside and started noticing all the little things I thought he was doing wrong, and began offering "helpful" suggestions:

  • "You're standing too close to the plate. Back up some."
  • "You need to step towards the pitcher, not third base."
  • "Keep your back foot planted."
  • "Choke up on the bat."

Well, after about five minutes in the cage, I succeeded in one thing -- thoroughly confusing him! But I also learned two valuable parenting lessons from that experience -- first, he's only nine... he'll figure it out; and second, he's really close to being a very good batter. He just needs to focus on making a few small adjustments.

And in all areas of our lives, switching gears from one type of an activity to another involves some changes. For marketers that are making the transition from traditional to digital, the same two lessons apply:

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Stop #9 in the Big Data Archipelago journey: the Investment Isle

“Data is a precious thing and will last longer than the systems themselves.” –Tim Berners-Lee, inventor of the World Wide Web

Last year, the International Institute for Analytics (IIA) and SAS published the research report, “Big Data in Big Companies,” written by Tom Davenport and Jill Dyché. For this report, they conducted extensive interviews with 20 companies to learn how big data is changing their analytics strategies, as well as the impact it’s having on their business.

In the report, one concern on the mind of executives was the return on investment (ROI) for big data. "Sometimes our ability to be more nimble as a business isn't easily quantifiable in hard dollars," says SAS Best Practices Vice President, Jill Dyché. "Sure, you can quantify the cost savings and revenue uplift as a result of faster speed-to-market, but enhancing a company's ability to innovate is a little squishier to put into numbers. In our survey, though, it was, in fact, the ability to innovate that compelled many of the executives we interviewed to invest in big data."

For years, we’ve been calculating the ROI for our traditional data warehouse and analytical systems by focusing on the costs of hardware/software acquisition, licensing and maintenance. How does big data impact this model?

The Investment Isle in the Big Data Archipelago

The Investment Isle in the Big Data Archipelago

A Big Data Best Practice for Investment

While hardware, software, licensing and maintenance costs continue to be important considerations, we need to go one step further for big data: Calculate ROI by focusing on new development processes, organizations and skills.

Here’s why: Big data is disruptive. Read More »

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The power of modernization - a customer success

Modernize your marketing with SAS Customer Intelligence solutions.Modernizing your software infrastructure is vital to remaining an efficient and competitive organization. Operating on legacy environments often leads to a disproportionate amount of time, resources, and money being spent attempting to maintain and/or operate these older environments.

Recently, we got the chance to hear from one of our customers about how thrilled they were with their modernization with SAS Customer Intelligence - having upgraded recently to the latest version of SAS Customer Intelligence Studio. Their results tell a great story about the power of modernization - 40 minutes saved per campaign, which translates to 28 hours a week! Multiply this by all the campaigns that run in a year and they are realizing 60,000 hours of time savings per year!

To find out more about the solutions we offer and they power they provide, please visit SAS Customer Intelligence.

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Do these 5 things to improve your marketing data

Picture of Ruth P. Stevens

Ruth P. Stevens

Having just gotten three emails in the last month that begin with "Dear Andrea," I can't tell you enough how important the topic of data hygiene is for marketers. I can assure you that addressing a person named John Balla as "Andrea" is the fastest way to get John Balla to disregard your message and unsubscribe.

I am happy to share this post from noted marketing expert Ruth P. Stevens about "data hygiene."  Considering the pivotal role of big data in today's marketing success, it's important to stop and consider the ways we acquire and manage our data because not doing it well causes problems that can balloon quickly.

Ruth's thoughts on this topic have already been surfaced in Biznology, on Target Marketing's blog and most recently on LinkedIn.  Her perspective fits right into our ongoing conversation here about customer analytics, so please read on.

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Are you happy with the quality of the information in your marketing database? Probably not.  A new report from NetProspex confirms: 64% of company records in the database of a typical B2B marketer have no phone number attached.    Pretty much eliminates phone as a reliable communications medium, doesn’t it?  And 88% are missing basic firmographic data, like industry, revenue or employee size—so profiling and segmentation is pretty tough.  In fact, Netprospex report concluded that 84% of B2B marketing databases are “barely functional.”  Yipes.  So, what can you do about it?

This is not a new problem.  Dun & Bradstreet reports regularly on how quickly B2B data degrades.  Get this: Every year, in the U.S., business postal addresses change at a rate of 20.7%. If your customer is a new business, the rate is 27.3%.  Phone numbers change at the rate of 18%, and 22.7% among new businesses.  Even company names fluctuate:  12.4% overall, and a staggering 36.4% percent among new businesses.

No wonder your sales force is always complaining that your data is no good (although they probably use more colorful words)? Here are 5 steps you can take to maintain data accuracy, a process known as “data hygiene:” Read More »

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Stop #8 in the Big Data Archipelago journey: the People Isle

 “If we have data, let’s look at data.
If all we have are opinions, let’s go with mine.”
– Jim Barksdale, former Netscape CEO

Have you read Tom Davenport’s “Data Scientist: The Sexiest Job of the 21st Century” article in the Harvard Business Review or Jill Dyché’s fun take-off, “Why I Wouldn’t Have Sex with a Data Scientist”? Who knew that a data job/role could have so much, um, appeal?! Could it be that we’re now living in our own Revenge of the Nerds?

All fun aside, it’s interesting to note that the data scientist discussion is saturated with some of the same questions we’re asking about big data:

  • What is a data scientist? What is big data?
  • Can we get by without a data scientist(s)? Can we get by without big data?
  • Why can’t we use the human resources we already have – e.g., business analysts and statisticians – for big data? Why can’t we use the technical resources we already have – e.g., data warehouse and analytical systems – for big data?

And speaking of big data “people,” you’d think it was all about the data scientist. But it’s not.

For years, “Evolve toward a competency center!” has been the battle cry of industry analysts and management consultants. And we’ve listened. We’ve established our BI and analytics competency centers by bringing the right people with the right skills and decision-making power to the table to manage our company’s reporting initiatives. And it’s been working.

But where does the data scientist and big data fit in now? Do we need to set up a new competency center?

The People Isle in the Big Data Archipelago

The People Isle in the Big Data Archipelago

A Big Data Best Practice for the People Involved

Back in 2011 when big data started grabbing headlines and keynotes, much of the discussion focused on Gartner’s 3Vs of big data and big data technologies. This went on for about two years – and then the discussion began to shift. Read More »

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Leveraging the internet of everything to create a better customer experience

Photo credit: The Digital Future of Retail, Merchandising Matters.

Photo credit: The Digital Future of Retail, Merchandising Matters.

The other day I received a letter in the mail. What was in the letter left me feeling depressed. It left me feeling inadequate, unprepared, incapable of mustering the mental and emotional energy to complete it’s request.

You see it wasn’t asking me to do something that I’d never done before. It asked me to do something that I had already relegated to extinction.

The letter asked me to find a pen (that worked), fill out a form by hand, write a check, find an envelope, write the address on the envelope, place the filled out form and the check in the envelope, find a stamp, lick and place the stamp on the envelope, walk the envelope out to the mail box and then wait for almost 20 hours for it to send (the mail man had come earlier that day). Since it was going across the country, it would be handed off between people, machines, and transportation vehicles and would probably be another several days until they received it. I also knew that a similar manual process would happen on the other end just in order to receive my communication. My efforts would not only take way longer than it should have to relay information and money, but it would likely be close to two weeks before the requestors would get what they wanted. Two weeks for what should have taken two minutes, leveraging today’s commonly available technology.

For several days, I honestly couldn’t bring myself to do it. My current systems and expectations have (perhaps prematurely) moved so far beyond those tasks, that I couldn’t find a way to smoothly integrate the process into my day. While late Sunday night, I actually honored the request, it felt like I was being forced to use an abacus instead of a calculator, or computer.

For effect, I am being a bit dramatic, but I’m not embellishing as much as it might appear.

But, how many of us ask our customers to perform analogous tasks with layers of unnecessary friction because we’re simultaneously stuck in the framing of the past, and the inertia of the present? What if most activities in the world were like a trip to the DMV? Thankfully, most are not. These experiences highlight the pain of a poor experience.

What makes experiences great?

The specific answers to this are highly contextual, and the subject of an entire field of study. However, at their aggregate level, great customer experiences come from delivering one or both of the following: Read More »

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3 steps to better marketing emails

As mentioned in a previous post about how we try not to annoy our customers, we really make sure we're not just going through the motions in complying with anti-SPAM laws. And it all has to do with how we regard customer relationships - they're valuable and we want them to be based on mutual trust and respect.

As a result, we pay close attention to what we say and how we say it because customer engagements are impacted by both content and delivery - whether it's initiated through search, by referral or as a result of one of our outbound messages. One of our most important outbound channels is email and we're not alone in that regard. Email was recently cited by MarketingProfs as the most-used digital marketing channel for 86% of respondents to recent research by Gigaom and Extole. That same report found that email was named the most effective channel for customer retention, building awareness, increasing conversion and boosting acquisition.

One key way for us to creating better marketing emails is using a tried and true method - through A/B tests.
Scott Calderwood and Becky Simanowski of the SAS Digital Marketing team.It seems like we're always testing something. And then we share our learnings among our colleagues and incorporate the new approaches across our different operating units. And with so many customer engagements happening online, it seems natural for us to ingrain testing as a standard marketing practice.

Two of our digital marketing team members, Scott Calderwood and Becky Simanowski, recently led an internal discussion that summarized 3 key findings from A/B tests we've done here at SAS and I thought I'd share them with you here: Read More »

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Stop #7 in the Big Data Archipelago journey: the Data Security Isle

“Human errors and systems glitches caused nearly two-thirds of data breaches globally in 2012.”
- Ponemon Institute and Symantec

Nothing has accelerated the proliferation and sharing of personal data more than the internet. Some may disagree, but unless you’re living a technology-free life – by choice or not – then it’s hard to dismiss the impact the internet has had on both our personal and professional lives. From email to social networks to online shopping and travel, we’re generating a crazy amount of online personal data every day. Who’s keeping an eye on that data and who’s protecting it?

The irony is that when it comes to our workplaces, we have historically held IT responsible for securing our corporate data. If there’s a data breach, we contact IT. If there are application or data access issues, we contact IT. If there are privacy issues, we contact IT (and probably Legal).

But is this really the right model for the internet age?

The Data Security Isle in the Big Data Archipelago

The Data Security Isle in the Big Data Archipelago

A Big Data Best Practice for Data Security

If we truly deem our data as valuable – whether it's corporate or personal, big or small – just like we do our financial investments, then perhaps securing data is not just IT’s responsibility anymore. Maybe it’s time for us to foster a culture where data is treated as a corporate asset. A logical place to start could be with social data – yours, your company’s and your coworkers. Who’s keeping an eye on this data and who’s protecting your company?

The answer should be “all of us.” Read More »

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Stop #6 in the Big Data Archipelago journey: the Data Governance Isle

 “Data that is loved tends to survive.” – Kurt Bollacker, data scientist

Awhile back, I had the pleasure of traveling to five countries in Europe to participate in a 10-day, SAS-sponsored executive roadshow. Jill Dyché, Vice President of SAS Best Practices, kicked off each event with a discussion on data governance, data management and treating data as a corporate asset. I then spoke about big data and going beyond the 3Vs, similar in concept to this blog series. After each event, we then had the opportunity to talk with SAS customers about their data governance and big data issues.

It is clear that data governance and data management continue to be important discussions – especially with big data on the scene. This was evident in Europe. While many companies have already developed (or are developing) an enterprise-scale data governance program, there’s some who still don’t understand its significance and/or are simply afraid to have the discussion. For those who do get it, though, they’re beginning to ask the question, “What do data governance and management look like for big data?”

The Data Governance Isle in the Big Data Archipelago

The Data Governance Isle in the Big Data Archipelago

A Big Data Best Practice for Data Governance

One casual observation I made on my trip is that Europeans, unlike their US counterparts, seem more cautious about jumping into one-off, sandbox-type, big data projects. They seem more interested in having the data governance and management discussion up front, or at least while they’re going along. In the US, a more common approach is to wrestle with big data first, then figure out how to govern and manage it later on – if the project proves successful. Perhaps there’s a happy medium. Read More »

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