Wednesday, February 24, 2016

Survey Finds Big, Dirty Challenge in 2016: Customer Data

Direct marketers know that quality data is at the heart of their success. Yet three-quarters of customer service, data, marketing, sales and tech professionals told the latest Experian Data Quality survey that they will be struggling with inaccurate data in 2016--undermining efficiency, customer satisfaction and profits. From a recent Direct Marketing News magazine report of Experian findings, respondents cited their main data quality problems as incomplete/missing data (60%), outdated info (54%), duplicate data (51%), inconsistent data (37%), and typos (30%)--and more than half attributed that bad data to human error. Indeed, when it comes to the biggest obstacles to improving data quality, respondents cite the two top challenges as lack of internal knowledge/skills and lack of internal human resources. As a data services provider, we're happy to see that underperforming data quality vendors is at the very bottom of the list of impediments to better data (cited by just 7%). So what kind of projects can we expect from clients this year if they join the push to tackle data issues? Those surveyed said they'd be working on data cleansing (37%), data integration (37%), data migration (31%), and data enrichment (31%). If you are still wondering if data quality is worth the investment, consider the top five reasons given for improving data quality: increasing efficiency (56%), enhancing customer satisfaction (41%), enabling more informed decisions (39%), saving on costs (39%), and protecting brand and reputation (34%)--all goals with a positive impact on the long-term bottom line. For more report details, read the DM News story at

Wednesday, February 17, 2016

Using B2B Data Segmentation for Sales Success

We work with many business-to-business clients on direct mail and data services projects, and a key task is list segmentation, selecting and personalizing by criteria with proven impact on sales success. A recent MarketingProfs article by Ed King, CEO of data automation firm Openprise, offers some great practical tips on using B2B segmentation for demand generation, starting with these top ways to segment B2B customers and prospects: 1) job level, which can be inferred from job title, winnows the decision-makers from the chaff of general leads; 2) job function, also inferred from job title, can start with coarse department divisions, such as Finance, Sales, IT, etc, or drill down by specialization within functional area, to tailor for buying process; 3) company size, either in terms of annual-revenue or employee-number ranges, helps target for product/service fit and offer; and 4) industry, using NAICS or SIC codes, selects best verticals for response/purchase. Segmentation can be used to achieve many key goals, King points out. Segmentation of the existing database helps develop a profile of best customers, so the business can market look-alike prospects by the same job, company and industry parameters. Segmentation also allows B2B marketers to go beyond targeting individual leads, who may not be the right contacts, to an account-based marketing that is more efficient. Segmentation, of course, supports more engaging personalization. Finally, segmentation permits money-saving suppression of low-value or low-response targets. These goals are not out of reach even for B2B marketers lacking quality segmentation data since they can turn to data services like ours for data appending and data cleaning/normalizing for effective segmentation. For the complete article, go to

Wednesday, February 10, 2016

Using Segmentation to Better Mine Donor Databases

We have helped nonprofit clients boost retention and fundraising response by segmenting their existing donor mailing lists for better targeting and personalization. And we've learned that effective segmentation has two strategic prerequisites: selecting the right segmentation parameters and having accurate data for those parameters. Unfortunately, surveys show that many nonprofits rely on an overly narrow donor segmentation strategy and ignore factors that could really improve response and engagement; for example, Eleventy Marketing Group recently highlighted a survey finding that while 80% of nonprofits segment by donation amount, other significant factors are frequently neglected (less than 15% said they always segment by interest, channel preference or demographics, for example). A January blog post by the Creative Suitcase nonprofit marketing/design agency gave a great summary of important individual-donor segmentation factors: donation amount, of course, but also donation timing (recency, frequency, patterns); area of focus or interest; preferred type of communication (and that means going beyond mail vs. all-or-nothing opt-ins to frequency and content options); age (older donors prefer direct mail, while millennials like a multi-channel approach, for example); and preferred donation channel (mail, event, online, etc.). So how can a nonprofit gather and maintain such information, especially preference and interest data, about donors? Online and mail donation form questions, online thank-you questions, event registrations and donor surveys are some of Creative Suitcase's suggested vehicles. We would add that demographic data, such as age, can be appended. For more on using donor segmentation to improve communications, see

Wednesday, February 3, 2016

Creating Loyalty: Using Retail's Most Valuable Data

Growing a loyal customer base is the holy grail of business, especially retail. A recent MarketingProfs infographic illustrates why: Existing retail customers spend 67% more than new customers, and increasing customer retention rates by 5% increases profits by up to 95%. One solution is a great loyalty program. Unfortunately, there is a disconnect between consumers (73% say programs should show the business's loyalty) and marketing execs (66% seek consumer loyalty, read dollars), which is why 97% of loyalty programs are about transaction rewards, and 77% of transaction-based programs fail in the first two years. The bottom line is that retailers need to better profile and segment loyal customers and then develop programs around their needs, not just their transactions--and that means improved data gathering and analytics. A Forbes magazine article by Bryan Pearson, president of LoyaltyOne, highlights nine loyalty trends for 2016 that we think can help refocus data efforts, especially since loyalty program engagement is getting tougher, with the average American household enrolling in 29 loyalty programs but active in only 12. Standard transaction-based points and discounts aren't going to cut through a crowded field to woo loyalty, so watch for a 2016 shift toward using data insights to offer high-value experiences, such as special events or early VIP access to sales, per Pearson. Plus, he notes that even transaction-based loyalty programs are changing shape; it's not just about cards and memberships now that there are apps to gather data and deliver personalized offers, including mobile one-to-one in-store specials (underscoring the need for integrated, multichannel data strategy). Indeed, retailers who truly maximize the value of loyalty data in 2016 will be those who use its insights across the business, not just in a retention silo, to align pricing, promotions and merchandise assortments to better address consumer needs, suggests Pearson. And he adds another way retailers can leverage data investment: Data generated by loyalty programs is a valuable product in itself, as evidenced by The Kroger Co.'s 2014 sale of $100 million in data to product suppliers. For the whole article: