Getting Donor Data Ready for Year-End Fundraising

Nonprofits are heading into their important year-end fundraising season when donor file prep and targeting can make a big difference in results. We wanted to pass along a recent nonprofithub.org post on key ways to maximize success with donor data, especially since these are areas where clients regularly rely on DBM Designs' data services. The first goal, as the article notes, is to have an accessible, updated, accurate and actionable database and donor management system. Besides name and contact info, it should include strategic targeting factors such as campaign performance, donor history, gift amounts, last gift dates preferred channel and demographics. Data services experts can help quickly aggregate, organize and clean existing donor data, and also help append missing data, such as demographics. The next key task is donor segmentation. Segmentation identifies groups by shared attributes in order to send each group the appropriate targeted message or campaign. Segments can be divided by giving level, last gift date, relationship with the organization, demographic information and more, and the article offers a handy "donor segmentation cheat sheet" for beginners. Of course, the segmented data is useless without a marketing plan, which should include fundraising goals; deployment timings; integrated use of channels such as direct mail, e-mail and phone solicitation; and targeting and creative messaging strategy. Targeted donor data and segmentation will then permit more effective creative via crafting of tailored, personalized communications that tap the donor's personal connection and history with the organization or cause. Plus, data can be used to tailor the rest of the donor experience, from the mailed response device or online donation page to expressions of acknowledgement and appreciation. For the full post, see http://nonprofithub.org/fundraising/5-steps-to-target-donors-for-year-end-fundraising-success/

Data-Driven Marketing Power Drained by Basic Mistakes

Data-driven strategy is an ideal that many marketers, especially in the B2B world, have not fully mastered. For example, a 2015 survey of marketing professionals by Ascend2 and ZoomInfo found that only 33% of respondents called their data-driven marketing strategy “very successful.” The good news is that just 10% said their data strategy was somewhat or very unsuccessful. Still that leaves a lot of room for improvement! What's preventing marketers from maximizing data success? In a recent martechadvisor.com post, Hila Nir, vice president of marketing and product at ZoomInfo, cited the three most common mistakes sapping data-driven marketing potential, with a focus on business-to-business marketing. No. 1 is wastefully "throwing the net too wide" and hauling in confusion. While there is a mass of multi-channel data you can gather and analyze, only some data and patterns are relevant to marketing success. So where do you start? Nir advises going to the foundation of the customer relationship--the actual customer contact--and building from there. The No. 2 error is failing to frequently refresh customer and prospect data. Data value erodes over time as basics such as mailing address, job title, phone number and e-mail change. Customer Relationship Management (CRM) software that stores lots of outdated legacy data can make the problem worse. And maintaining data quality is a big job that only grows with the size of the database. That's why 79% of the most successful data-driven marketers in the survey said they outsourced some portion of data management. Finally, mistake No. 3 is simply failing to take full advantage of customer and prospect data to improve cost-effectiveness and ROI. Trying to find a path through the data weeds to ideal customer targeting can certainly be daunting and strain internal resources--which is also why many successful B2B marketing efforts turn to consultants for database analysis. Needless to say, DBM Designs is among the data service partners who stand ready to assist! For the full article, go to http://www.martechadvisor.com/articles/audience-market-data/3-mistakes-that-kill-any-datadriven-marketing-strategy/

Personalization Driven by Bad Data Ends Up Crashing

Personalization is a fundamental necessity for direct marketing response today. So why do personalization efforts still flop? It's usually a data problem. A recent post by Spider Graham for bizjournals.com highlighted five common personalization mistakes and illustrates our point. First, pretending to know a recipient when the marketer clearly has nothing more than a name is a response killer. True personalization is about crafting message, offer and value proposition based on understanding the target and his or her needs--which requires recent, multifaceted, quality data. On the other hand, getting the name right is still the first, most basic requirement. Using the wrong name or a misspelled name is a data sin, but even using the wrong version of a name can backfire, especially with opt-in e-mail or telemarketing, Graham points out. Spam suspicions rise when someone who always subscribes as Bob is addressed as Robert. That's why it's important to consider list data sourcing when personalizing, especially in terms of hygiene and rented versus house quality. Third, Graham reminds that marketers are chasing moving targets; many attributes, from address to relationship with a brand, change over time. Good personalization relies on up-to-date data about multiple demographic factors and purchase patterns. A promo for stuffed toys to a household where all kids are grown and gone stirs up nostalgia not dollars. Fourth, don't lie and imply a relationship that doesn't exist based on a one-time visit or query, warns Graham, or "come back" and "we miss you" will not only alienate but waste an opportunity to start a new relationship. Finally, check your basic data quality! Dedupe, normalize, update and watch for missing data fields as well as faulty fill logic so you don't end up with "Dear FirstName" or "We miss you, N/A." The good news is that the worst personalization errors can be avoided by committing to smart data hygiene, logic and processing. See the complete article: http://www.bizjournals.com/bizjournals/how-to/marketing/2016/06/5-personalization-mistakes-marketers-make.html

Are Duplicate Fields Hurting Your Database Marketing?

A basic requirement of cost-effective direct marketing is elimination of duplicates, meaning multiple database records for the same person or company account. But marketers today need to watch out for another, trickier duplication challenge: duplicate data fields. Expanding use of multi-channel, multi-sourced data fuels the problem. The same prospect or customer record is often enriched by data from different online and offline sources--data appending services, lead-gen services, list rentals, predictive and lead scoring services, e-mail validation services, call center entries, online ad and social platforms, events, and so on. The marketer may intend to validate, update and unify this data, but efforts are delayed or incomplete for whatever reason. Then the marketer gets ready to launch a campaign and discovers many contact records have two job titles or four industry codes or three e-mail addresses. If the data entries are not clearly dated and sourced, the marketing team has no clue which data are the most up-to-date, accurate and appropriate for targeted promotion! We were pleased to see a recent MarketingProfs article by Ed King, CEO of the data automation firm Openprise, offer cogent advice on avoiding this costly problem. Obviously, marketers should first strive to unify field content promptly while the data is fresh. If data unification must be delayed, new data should be labeled by its source and age for use in future data consolidation decisions. Whether field data unification is immediate or delayed, the marketing team needs to agree on a data-unification logic. King advises that this logic should be based on at least three key factors: source authority (giving priority to trusted data sources); source focus (preferring sources more aligned/specialized for the marketer's industry/target); and age of data (for example, in B2B, more recent contact name or company size is likely to be more accurate). Consistency and scalability are the goals; ad hoc, manual record decisions are not only less efficient but less likely to yield optimal overall results. While unifying data in fields, the database process should also normalize data so formatting and coding are consistent. Plus, a smart database effort can remap field content for better targeting. King provides the example of consolidating 2,000 industry codes into 10 custom definitions that better fit market targets. For the whole article, see http://www.marketingprofs.com/articles/2016/30069/your-duplicate-data-problem-has-an-evil-twin-that-is-much-worse-duplicate-fields?adref=nlt060816

Spring-Clean That Sales Funnel to Keep Leads Flowing

If lead flow has slowed and lead performance is spotty, maybe it's time for spring cleaning of the sales funnel. A recent business2community.com post by Megan Totka, chief editor of ChamberofCommerce.com, offers a recipe for how even a small business can clean and polish its sales process. Start by purging old, unresponsive leads--plus, we would add, update contact and targeting information, and clean up inaccuracies and formatting of retained prospect data. Then create a time frame for contact and follow-up so leads don't go stale. Totka points out that the odds of qualifying and converting a lead increase by 21 times if called within 5 minutes, compared to 30 minutes. Obviously, speedy entry of new, qualified leads is an important system goal. But those incoming leads need good pipeline processes not only for lead entry but also lead qualification and management. CRM software can help, but it boils down to deciding on basics for turning leads into sales opportunities. Totka lists some key questions to ask: When leads come in from various sources, where do they go? How much time do you have to enter them? Who or what qualifies them? Who or what moves them along in the funnel? How much time do sales agents have to follow up with the leads? With those issues in mind, evaluate new or existing sales processes for problem areas, places where leads leak out, or stick and go stale. Still, no matter how good the sales funnel, it only works if a steady flow of leads is entering, and that means adjusting marketing strategy to boost qualified lead generation--testing and optimizing targeted e-mail, direct mail, social media and online promotions. If qualified leads aren't converting despite good targeting, then seek prospect feedback. Is it an overly complex sales process or something more basic like noncompetitive pricing? Test and readjust the lead gen and sales processes, adding lead nurturing, in the form of follow-up e-mails or calls, to move prospects past sticking points. However, even if the sales pipeline is pleasingly full, don't forget to keep purging unresponsive and inaccurate data to prevent costly clogs! For the complete article: http://www.business2community.com/sales-management/10-steps-cleaning-reigniting-sales-funnel-2016-01479262#3dI68EPFloBMSoco.97

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 http://www.dmnews.com/dataanalytics/managing-customer-data-in-2016/article/469162/

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