Customer Intelligence Blog

At 2012 Loyalty Expo hosted by Loyalty 360 Altair Customer Intelligence conducted a survey. We asked everyone we met, “What is your largest hurdle: Data Integration, Customer Analysis, Predictive Modeling, Performance Measurement or Access to Reports?” We had 68 respondents to our survey and as we expected Data Integration was the top hurdle followed by Customer Analysis. We suspect as everyone gets a handle on data integration the hurdles will progress down the line.

Altair understands the daunting task of Data Integration. With more avenues than ever, the ease of data capture, and the inexpensive storage companies collect more information than ever, “Big Data” as it is being called. Altair has been handling Big Data since 2001, we assimilate well over a billion rows of data each month into 5 major indexed files ranging in size from 21 million businesses to 200 million consumers. This data doesn’t come to us ready to merge. We’ve taken years to perfect our cleanse and merge technology. Take advantage of our experience and have Altair handle your integration.

Once integrated Altair has the tools and experience to perform Customer Analysis, build Predictive Models, develop and execute Performance Measurement and grant access to robust Reports.

Altair Customer Intelligence is a proud member of Loyalty 360 and will be exhibiting at the Loyalty Expo for the 2^nd time.  The Loyalty Expo is a great place to meet counterparts and experts in the field to learn and grow.

In addition to Mark Johnson’s, always insightful, keynotes we have attended sessions hosted by the following and they were excellent:

B2B-Focused Session: Shifting from Satisfaction to Advocacy in a Member Organization

Samantha Keyes, VP Corporate Marketing – VHA
Melinda Gladitsch, Managing Director, Client Services – hawkeye

Latest Findings in Loyalty Research: What Does it Mean for Marketers in 2012

Mark Johnson, President and CEO – Loyalty 360
Tim Suther, Chief Marketing Officer and Senior Vice President – Acxiom
Pamela Prentice, Chief Researcher – SAS
Emily Murphy, Researcher – Forrester Research

Philosophy on Loyalty: Essential at the Confluence of Mobile, Hyperlocal and Daily Deals!

Jay Loeffler, Director of Corporate Strategy – Cox Target Media & Valpak
Bob Fetter, Senior Vice President – Pluris Marketing

We look forward to seeing you at the Expo.  We’ll be in booth #505.  Look for your poker chip in your welcome bag to participate in “with Altair everyone wins” giveaway.  Roll the dice to win an NFL Jersey, iPod touch, and more.

If you are looking for improvements to your marketing campaigns, predictive modeling can oftentimes give you just the lift you need.  If you have the time, the data and the money, a custom predictive model will usually yield the best results. For the rest of you, a product-specific shelf model may be just the ticket.

First, what is a shelf model?  A shelf model is a predictive model built on product or channel-specific data that can be used by any company for their direct marketing campaigns.  Shelf models are best used in customer acquisition, customer cross-sell and customer attrition scenarios.

The best aspect about shelf models is they can be deployed immediately and the initial cost is just the cost of the data (mailing list or email list).  On the other hand, custom models can take weeks to develop (most of our custom models are completed in less than 2 weeks) and even longer to validate and perfect.

At Altair, we have had success in banking models for home equity, checking and auto lending, in insurance for auto, home, mortgage insurance, Medicare Advantage and long-term care, in mortgage for prime refinance, FHA/VA in the market, and reverse mortgages.

Another great benefit for shelf models is to bridge the time between completion of a custom model.  By employing a crawl, walk, run strategy, you can start with shelf models and move into custom models much quicker than just waiting on a custom model.

Unless you’ve been on the moon, you probably heard that Netflix has done some damage to its brand recently. First, they announced a price hike, increasing the price most people were paying by 60%. Then, they followed that up by announcing they were separating their business into two distinct (and separate) offerings.

They made a lot of people angry. A lot of people left, or downgraded their service. They took a beating in the stock market and lost shareholders a ton of cash. How did they justify these moves? With research. They said their research told them more people used the streaming service (or were moving that direction), and the DVD business would soon be obsolete. Therefore, in order to keep what might one day be a dying business from tearing down a profitable one, they separated them. It all sounds good on paper, but they forgot one thing – their customer’s opinions.

Sometimes we need to look past what the data is telling us, and listen closely to our customers. Had Netflix done this, they might have realized that their customers weren’t upset just over a price hike, but more over the perceived value (or lack thereof) of the service. The rate hike may have made sense on paper, but wasn’t justified when their customers already felt they weren’t getting the best deal.

Remember that part of great marketing is knowing your customer – not just the transactions, but the needs, behaviors and attitudes as well. Before you make the next big decision, consider that along with the financial data. It will be wiser and more informed.

I’m a fan of Marketing Charts. I get their update everyday, with cool charts and facts from the world of marketing. Today’s top chart caught my eye. It struck me as funny that a survey could claim more consumers are “loyal” to online sites that provide regular discounts. In fact they go as far to say that they are more loyal to sites that offer regular discounts, versus the occasional discount. I think they have their definition of loyalty wrong. Here’s the link to the full chart, or view a portion below.

This survey appears to be about use – which is only a portion of what loyalty is to a brand. I, too, use online sites more often when there is a discount.  That doesn’t mean I’m loyal. At best, it means I’m a mercenary trying to get the best price on something. Loyalty is “choosing one brand above another regardless of price based on how that brand performs for you, fits into your life, or even aligns with your aspirations.”

How do you measure that? Simple. Ask them questions. To develop a sense of who your loyal customers are, and why they are loyal, you have to ask them. Ask them questions in these categories:

• Overall satisfaction with the brand
• Product-level satisfaction
• Timeliness of delivery
• Customer service process satisfaction
• Returns and exchange process satisfaction

True loyalty indicators come from questions about:

• Interest in new potential products and services
• Willingness to repurchase
• Willingness to recommend
• What influenced the purchase

When you combine the attitudes and behaviors from a survey, data from your client file, and outside data, that is how you end up with the best way to discern loyalty.  You will weed out mercenaries and focus on the consumers that truly engage with your brand.

How well do you know your customers?  Oh sure, you probably (hopefully!) know things that happened at your register like what they buy from you, how often and how much.  But what else do you know?  And how would it help you target your customers to learn more about them.

The other day, I was shopping at Harris Teeter.  Okay, I confess—there is no ATM in my neighborhood, so I ran into the store with my son and grabbed the first decent thing I saw.  It just happened to be a pack of Double Stuff Oreos.  The Halloween edition with the Orange filling instead of white.  So, my son and I head over to the self-pay check-0ut line.  I dutifully scan my Harris Teeter VIC Card—I’m sure Harris Teeter spent many hours and dollars coming up with the name VIC, but I have no idea what it stands for other than I have to use it to get great discounts.  Anyway, after scanning my VIC card and letting my son scan the barcode on our soon to be devoured pack of Oreos, the register asks me “Do you have any coupons?”  My son hit the No button.  Next, the screen asks me “Are you eligible for our Over 60 discounts?”

Whoa!!??  Hold everything.  Why is this cash register wondering if I’m 60?  Do I look 60?  And why, after many trips to this Harris Teeter did they just now decide to ask me if I’m 60 years old?  Do a lot of 60 year olds buy Halloween Double Stuff Oreos?  This is all going through my mind in a flash.  I must admit, I was a bit offended.  I don’t know if any other Harris Teeter customers are feeling the same way or not, but it made me wonder.

Age is an easily obtained demographic.  First, you could just ask for it on your loyalty application.  Or you could simply append it from voter, drivers license, and self-reported data.  It is the most accurate compiled demographic category–other than gender.  The great thing about age is it’s not going to change.  So, once you apply it to your file, you have it.  Then, you can begin offering discounts–like Harris Teeter is–based on age without making some customers feel left out.  Also, you can begin segmenting your customers by age based on purchased habits and begin targeting your marketing better based on what your customer wants.

One final thought.  Can you imagine having your store clerks ask your customers, “Excuse me sir, are you 60 years old?  I want to see if you are eligible for our 60 Rewards Club.”  If you can’t foresee having your clerks ask, don’t have your cash register or kiosk ask either.  There are much better ways of getting the information you need.  Oh yeah, and drivers license data doesn’t lie!

Seeing the strong rumor that Klout raised $30 million on a valuation of $200 million got me to thinking about the future of endorsements and loyalty programs.  This 3 year old company has a vision of their Klout becoming like a credit score.  Klout calculates how socially influential a person is on the web.  Just think, Loyalty Programs can target individuals for special rewards based on their Klout score.  Highly influential people will get discounts or endorsement deals based on Klout.   Klout runs on Twitter, Facebook and LinkedIn.

This model allows brands to truly leverage the strength of peer recommendations.  We’ll all trust someone we know over a generic add or celebrity endorsement.  Audi, Disney, Popchips and Lot18 all are using Klout Perks for the launch of products.  It makes total sense!

Not only will your product be supported by people who are trusted by peers you’ll be collecting enormous amounts of data that will help you better understand why they like it, what influences the purchase by the peers, what purchases are made and for how much, and the ability to align the reward accordingly. Integrating this with offline data only makes your profiling, segmenting and predictive capabilities stronger.

Brilliant!

How many times have you been the recipient of a mail piece addressed to someone else? What usually crosses your mind when this happens? If you’re in the Direct Mail Marketing business, you think of the steps that did or did not take place that should have before this piece went out. But if you’re NOT in the business, which sums up the majority of the population, you most likely toss this piece in the trash without much thought, other than a glance at the sender’s name.

While the advertising element is still there, three very crucial elements are now at stake: Credibility, timeliness and relationship. Do you think more, or less of the companies that you now know have incorrect information? On a credibility scale, these companies have dropped a notch or two in most recipients’ books, simply because their data is wrong. If they can’t get your name right, can you trust them?

Let’s turn the tables around for a minute and move from the prospect’s perspective, to a business perspective. Obviously data integrity is of utmost importance with any mail campaign, and many companies have become more aware of NCOA processing, mainly due to more stringent regulations set by the USPS since 2008 (and of course, the postal discounts that come with that coveted NCOA certificate).

But the benefits of NCOA processing go far beyond a postal discount.

While maybe you suppress your current customers from your upcoming mail campaign, do you still know where your current customers live?

With Altair Customer Intelligence’s unique product line-up, we cater to client’s needs by outlining NCOA specifics. Here are some key elements that you should always ask when it comes to NCOA:

1. What is your NCOA time-frame window?

NCOA tracks moves in blocks by months. Most NCOA processing tracks moves within the past 18 months. Anything beyond may or may not be captured. While 48 –month processing is available, it is not typically the standard.

2. Should I NCOA my customer file?

You should always NCOA your customer file for a mail campaign, but it is at your discrepancy whether or not to NCOA the file for suppression purposes. There are many moves that might not have a forwarding address. At Altair we give the option to retain original addresses as well as new addresses in order to reduce the chance of re-prospecting your customers.

3. When was my data file processed through NCOA?

This is important to receive the postal discount. The current USPS standard is that your data file be processed through NCOA in the past 90 days.

4. What happens to the records that match in NCOA (the movers)?

This is an important aspect of the NCOA processing. Depending on your product and projected prospect group, the decision to keep or drop these records is an important decision. At Altair our experienced sales team can coach you through these decisions in order to achieve your goal. While a New Mover campaign would benefit from keeping the records with new addresses, a Home Refinance campaign might not. There are many ways that this processing could also work as a suppression step when trying to eliminate movers within a certain timeframe.

John Wanamaker famously said that “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.”

Most companies collect enormous amounts of data about their customers but few use this data effectively to improve their marketing efforts.  Data about the results of marketing campaigns is often not turned into actionable reports and even then it often does not make it to an audience that can utilize the information.  Luckily it is easier today to discover which half of your budget is being wasted.

Tools to analyze data and create interactive reports for distribution to wide audience have made it possible to make sense of the piles of data collected by companies.  Until recently these tools were out of the price range of all but the largest users.  Now with the advent of software as a service (SaaS) these powerful tools can fit into even the smallest budget.

Altair has partnered with one of the leading BI reporting tool providers to add online analytics and reporting to our suite of marketing services.  Sonar provides the best information at the correct level, from the executive to the analyst. We have a proven track record of rolling out analytical dashboards that allow users to easily drill into the data and find where their marketing dollars are being misspent and how to place marketing budget effectively.

Everyone in the Customer Intelligence world is used to the term Customer Data Integration (CDI).  Now, data from the digital age needs to be integrated, Social Data.  Social Data by its very nature already links a persona to a brand or sentiment of an event or brand.  The researcher, like me, will use brand sites, reviews and “friends” opinions to decide on large purchases.  The next generation is adding sentiment to the mix via world of mouth, which I’ll lump blogs, Facebook, Twitter and the occasional actual conversation.  The question is how do you tie this together?  How do you stay on top of the Earned, Owned, and Search Channels?

Make the most of the content generated by linking it to your “offline” data.  Including Social Data in the CDI mix takes more finesse than traditional CDI.  Some data such as comments and reviews generated by users with shared information on your brand site or Facebook page can be directly linked while other content will need categories or buckets built to collect them such as using the combination of channel, location and/or product.  Knowing this will allow you to optimize your communication and SEO.

The Infographic below is a study conducted by beyond, www.bynd.com.  Understanding this is step 1, step 2 is integrating the data, and step 3 is taking action!

Social Data