Using Data, Technology & USPS to Rev Mail Response

Recent research provides compelling reasons to include direct mail in marketing plans--and also highlights opportunities to further pump response and ROI. Direct mail response rates actually jumped in 2016 per the Data & Marketing Association (DMA) 2017 "Response Rate Report," hitting 5.3% for house lists and 2.9% for prospect lists, the highest levels the DMA has tracked since 2003. Also consider last year's InfoTrends' direct mail statistics: 66% of direct mail is opened; 62% of consumers who responded to direct mail made a purchase within three months; and 56% of consumers who responded to direct mail went online or visited the physical store. But direct mail is expensive, and response is no slam dunk, so marketers must plan carefully to leverage positive trends. Luckily, 2017 offers data and print technology options, and U.S Postal Service support, to aid in direct mail success. We suggest committing to six key steps: First, start with data quality. That requires updating, cleaning and aggregating the customer database. Look for data gaps and append important targeting factors, such as contact info, demographics or firm-ographics. Second, analyze the data to identify and profile your best customers and their attributes, preferences and transactional history so that you can find and target lookalikes in acquisition, as well as tailor more profitable retention. Third, use your data to create effective targeting and personalization with tactics such as segmentation, variable data printing and timely triggered mail. Segment the audience into target mail groups, based on factors ranging from age and gender to purchase history. Use variable data printing technology for hyper-targeted messaging with multiple variable-content fields. You also can automate digital-activity mail triggers so that, for example, a relevant postcard is sent within 48 hours of an online purchase. Fourth, use print technology's PURLs or QR codes to leverage multi-channel investment, boost response ease, and create a seamless brand experience by linking physical mail to website, mobile and social. Fifth, test innovative creative that will stand out in the mailbox. Summer Gould, president of Eye/Comm, recently offered some suggestions in Forbes magazine, including Augmented Reality, dimensional mail, "endless folds" pieces, and video mailers. Finally, take advantage of the U.S. Postal Service's postage discounts and incentives! In 2017, programs include Earned Value; Color Transpromo; Emerging & Advanced Technology; Tactile, Sensory & Interactive Engagement; Direct Mail Starter; and Mobile Shopping. For details: https://www.usps.com/business/promotions-incentives.htm

Marketers Should Stop Snub of Third-Party Data

Many data-driven marketers seem to suffer from a costly bias that focuses on first-party and second-party data and gives short shrift to third-party data. For example, an April business2community.com report of the "Data-Driven Marketing Benchmarks for Success" study by Ascend2 and ZoomInfo shows that a company’s internal first-party data is used by 86% of data-driven marketers, but only 49% use data from marketing partners, 32% use data from channel partners, and a mere 27% use data from third-party vendors. Why the third-party data snub? Marketers may assume that first-party data is more powerful, but that power depends on data quality and completeness. In fact, third-party data has a vital role in enriching first-party data by adding key targeting information. Third-party data sets can be appended to first-party data to correct and fill in missing elements such as e-mail addresses, phone numbers, lifestyles, demographics, purchase indicators and more to strengthen customer insights. Second, while first-party data is more powerful for certain marketing goals--such as loyalty programs, targeting and retargeting existing customers, or profiling best customers--it's not going to provide a mailing list of new prospects for growth! Marketers can rent quality third-party data and segment these specialized data sets to target prospects by factors such as demographics or firm-ographics, trigger events, location, recency, purchase history, and more. Marketers also may assume that even second-party data from partners is of higher quality than third-party data. First, that ignores the inherited quality problems and integration issues of second-party sources. Second, more high caliber third-party data is available today than in the past. Marketers can further ensure third-party list quality by working with a data-independent provider, by selecting aggregated data from multiple quality sources and files, and by making sure all data is frequently updated and hygiened. For more on the power of third-party data for direct and digital marketing, read http://www.datasciencecentral.com/profiles/blogs/the-power-of-third-party-data

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 http://www.marketingprofs.com/articles/2016/29267/four-practical-segmentation-tips-for-b2b-marketers

Turn Aging Behavioral Data From Problem to Opportunity

Database marketers focused on quick response to customer behavior tend to discount aging or expired behavioral data, creating an ongoing "data atrophy" problem. And that's a mistake in our experience. We agree with veteran database marketer Stephen Yu's recent Target Marketing magazine post, which argues that marketers need to see their aging and expired behavioral data as an opportunity rather than a problem. Issues arise because while targeting is improved when demographic or "firm-ographic" data is combined with behavioral data (transactions and clicks, for example), behavioral data is both harder to collect than geo-demographic data, which can be appended to fill gaps, and has a shorter shelf-life. The value of a hotline list evaporates quickly, and delayed response to real-time mobile or online actions can misfire, even backfire. But aging behavioral data still has value, and formerly hot data can be warmed up--especially if handled appropriately as Yu suggests. One way is to go from simple time stamps to measurements of intervals between events. How many weeks have elapsed since the last purchase? What are the average number of days between transactions? What is the average number of weeks between new product release and actual purchase? Marketers should also measure by channel to catch when an in-store or catalog buyer becomes an online buyer, and for which items. Yu points out that by collecting, maintaining and transforming historical behavioral data, marketers can use it for more effective targeting and personalization. Scored behavioral data become predictors in models identifying “cutting-edge buyers,” “bargain seekers,” “online buyers of repeat items,” “infrequent high-value customers,” “frequent small-item buyers,” for example. Yu concludes: "Today’s data become historical data in a blink, but we still have a lot to mine there. And such mining is possible, only if we arrange the data properly and let it age gracefully using statistical techniques. That is the way to personalize messages constantly for everyone, instead of reacting to real-time data only sporadically for a fraction of your audience." For the whole post, see http://www.targetmarketingmag.com/post/data-atrophy/

Don't Let Data Glitches Stymie B2B Lead Efforts

Business-to-business marketers dedicate chunks of budget and time to gathering qualified leads. Unfortunately, we've seen basic data problems undermine the effectiveness of hard-won B2B prospect and customer databases. So we'd like to pass along a recent MarketingProfs article alerting marketers to six of the most common data pitfalls. No. 1 on the list posted by Rob Manser, acting director of marketing at contact validation firm Service Objects, is relying on a single contact method in lead data. Focusing solely on e-mail outreach, for example, increases failure from address errors or poor channel response. By gathering or appending multichannel contact options--phone, e-mail and mailing address--the chances of connection climb. As Manser points out: "An e-mail or a phone call might never be returned, but a clever direct mail piece may catch a prospect's eye." Problem No. 2 arises from incorrect data gathering--incomplete, typo-riddled, misformatted or just plain bogus contact information. It doesn't mean all bad-data contacts must be tossed; many can be cost-effectively salvaged today via data verification, validation and appending software. Pitfall No. 3 is out-of-date information. Valuable contacts change companies, move to other locations in the same company, change titles and departments, etc. Frequent and thorough contact-data updating is required. That said, even when info is technically correct, Pitfall No. 4 occurs because data is not contact-specific enough; using a headquarters phone and address instead of the contact's division location will miss response in a geo-targeted campaign, for example. No. 5 on Manser's list of prospecting mistakes: Lead data that doesn't include a company's key targeting criteria--such as title or company size--which creates costly sales and marketing misfires. The final error compounds all others: allowing a contact database to become a pool of wasted opportunities by failing to fix data problems. Manser argues that there is no excuse now that marketers can turn to database services for quick, automated data-appending, data-verification and data-validation programs for clean-up--and we agree!  For more: http://www.marketingprofs.com/opinions/2015/28978/six-huge-lead-generation-pitfalls-that-are-hurting-your-business