Prep for 2020 Marketing With Clean, Personalized, Predictive Data

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As 2019 closes, AccuList’s data services clients have a year’s worth of multichannel customer, campaign and sales information to analyze and inform 2020 plans. So what are the big trends that the data pros foresee will deliver maximum ROI?

Data Hygiene Issues Remain a Priority

Clean, up-to-date, quality data is still the basis for good marketing analyses and campaign planning. A November Business2Community post by marketer Dan Moyle helpfully summarized the key data cleansing tasks that businesses need to undertake to hit the ground running in 2020. After all, it’s estimated that 20% of the average contact database is dirty, so this is not a trivial effort. Increasing marketing efficiency, response and customer loyalty, requires removing data errors and inconsistencies. Start by monitoring data for issues such as duplicates, missing information or bad records to figure out how and where they are occurring. Then standardize processes at each entry point. Next validate the accuracy of data across the database by investing in data tools or expert data services, and commit to regular cleansing and maintenance of data quality. Identify and scrub duplicates. Once the data has been standardized, validated and de-duped, improve its analytic value by using third-party data appending sources (to flesh out demographics, psychographics, firm-ographics, purchase history, etc.) for a more complete customer picture. Establish a feedback process to spot and update, or purge, incorrect information, such as invalid e-mail addresses identified by a campaign. And communicate standards and processes to the whole team so that they understand the value of clean data in segmentation targeting, lead response, customer service and more.

Using Data for an Agile, Personalized, Customer-Centric Edge

Data trends figured prominently in the 2019 Martech Conference and a recent article from martech firm Lineate highlights a few keynotes, such as the role of data in personalization. When a 2019 RedPoint Global survey of U.S. and Canadian consumers finds that 63% expect personalization as a standard of service and want to be individually recognized in special offers, personalized marketing is clearly a competitive essential. Expect to see use of Artificial Intelligence (AI) and machine learning (ML) increase in 2020 as personalization tools. Machine learning is when a computer is able to find patterns within large amounts of data in order to improve or optimize for a specific task. For example, for more personalized offers and messaging in acquisition, this means using ML to recognize if people from certain areas are more likely to respond to a specific offer or which past high-response special offers may resonate in future . Personalization is also key to the customer-centric experience proven to drive long-term retention and brand loyalty–as opposed to getting the same message again and again. When personalization is combined with elimination of data silos and creation of a single customer view across channels, marketing becomes especially powerful. Indeed, integrated database development and the elimination of data silos are also key to the growing “agile marketing” trend. Agile marketing breaks down team silos (which assumes breaking down data silos) in favor of teams focusing on high-value projects collectively. According to a 2018 survey by Kapost, 37% of businesses have already adopted agile marketing, and another 50% said they haven’t yet become agile but expect to be soon.  

Taking Data Insights From Retroactive to Predictive

Looking ahead to 2020, marketers should also consider adding predictive modeling to their toolkit if they haven’t already done so. Why? A study by ClickZ and analytics platform provider Keen found that 58% of marketers using predictive modeling experienced a 10%-25% ROI lift, while another 19% saw more than a 50% uplift. While retroactive campaign data can be very useful for reporting and results analysis, it’s not always as good for informing future multichannel directions, for optimizing media investments, or for quick execution and performance assessment. In fact, nearly 80% of Keen/ClickZ survey respondents felt they’d missed opportunities because of slow or inaccurate decision-making using non-predictive data reporting. For example, standard data analysis often fails to span all channels (e.g., online video vs. store-level programming) and mistakenly gives most credit to last-click channels such as search or transactional activities. In contrast, the Keen/ClickZ survey found marketers using predictive modeling boosted results in multiple areas, including a better understanding of the target audience (71%), optimizing of touchpoints on the customer journey (53%), and improving creative performance (44%). Predictive modeling also can help businesses synthesize large volumes of data, a key concern for many; in fact, 38% indicated their current measurement solutions do not support the scale of their data.

 

Make Clean Data a Top Priority for Effective B2B Marketing

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As business-to-business marketers craft their fiscal 2020 budgets, it’s important that complex issues such as analytics, automation or AI do not distract from a core investment for achieving ROI: clean data. Certainly, AccuList stresses to all its list hygiene and management clients, whether for house lists or rental prospecting lists, the importance of data quality for targeting and response, and a recent blog post by b2b data management firm Synthio confirms the basic steps for data hygiene.

Start With a Clear Data Plan

When 94% of B2B companies suspect inaccuracy in their databases, any marketers who do not prioritize data hygiene have their heads in the marketing sands.  That starts with a data plan. A good data plan will decide on the data-quality key performance indicators (KPIs) needed to achieve business goals. The plan will survey existing contact and account data and determine how to measure health in terms of data accuracy and completeness and how to maintain data hygiene tracking on an ongoing basis. It will look to see if there are important parameters for KPI success that the existing data does not address.

Standardize, Validate and De-Dupe Contact Data

What are the basics of data health and hygiene? Before cleaning data even begins, marketers need to check that important contact data at the point of entry or download is standardized. This will make it easier to catch errors and duplicates and to merge data from multiple sources. There should be a standard operating procedure (SOP) that defines fields, formats, and entry or upload processes to ensure that only quality, standardized data is used. The next step is to validate the accuracy of the data. Although a manual process might work for a small database, and there are tools and imported lists for cleaning data, advanced data hygiene is probably best handled by experts like AccuList, which can match contact addresses against USPS verification standards and change of address databases as well as update e-mail address changes. With standardized, validated information, data sets can be seamlessly merged and purged of duplicates. Why worry about duplicates? Duplicate records hobble CRM efforts, waste dollars in marketing campaigns, undermine the Single Customer View essential for targeting and response tracking, damage customer relations and brand reputation, and result in inaccurate reporting that can mislead marketing strategy.

Append Missing Data Parameters

Most b2b house databases have data for each record, such as contact first and last name, e-mail, company name and business address. But complete data for all records may be spotty, and some desired data may be missing altogether, such as title, phone number, company annual revenue, tech stack, purchase history, etc. Wouldn’t it be great for targeting and response to fill in the blanks? Data appending can enhance a house file with hundreds of variables from outside lists, including business “firm-ographics” on revenue, industry, employee numbers, etc.; opt-in e-mail, and telephone numbers. Self-reported LinkedIn data is another source that can be used. For more detailed data cleaning tips, see Synthio’s full article.

Predictive Analytics Can Harness Data for Marketing ROI

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Beyond list brokerage, AccuList can support direct marketing clients with “predictive analytics,” meaning scientific analysis that leverages customer and donor data to predict future prospect and customer actions. It will scientifically “cherry-pick” names from overwhelming “big data” lists and other files. For example, AccuList’s experienced statisticians build customized Good Customer Match Models and Mail Match Models to optimize direct mail results for prospect lists, as well as one-on-one models for list owners to help acquire more new customers or donors. Plus, predictive models aid other marketing goals, such as retention, relationship management, reactivation, cross-sell, upsell and content marketing. Below are some key ways predictive analytics will harness data for better marketing ROI.

More Swift, Efficient and Effective Lead Scoring

Lead scoring is too often a sales and marketing collaboration, in which salespeople provide marketers with their criteria for a “good” lead and marketers score incoming responses, either automatically or manually, for contact or further nurturing. Predictive analytics will remove anecdotal/gut evaluation in favor of more accurate scoring based on data such as demographics/firmographics, actual behavior and sales value. It also speeds the scoring process, especially when combined with automation, so that “hot” leads get more immediate contact. And it allows for segmentation of scored leads so that they can be put on custom nurturing tracks more likely to promote conversion and sales.

Better List Segmentation for Prospecting, Retention and Messaging

With predictive analytics, list records can be segmented to achieve multiple goals. The most likely to respond can be prioritized in a direct mail campaign to increase cost-efficiency. Even more helpful for campaign ROI, predictive analytics can look at the lifetime value of current customers or donors and develop prospect matching so mailings capture higher-value new customers. Predictive analytics also can tailor content marketing and creative by analyzing which messages and images resonate with which customer segments, identified by demographics and behavior, in order to send the right creative to the right audience. Finally, analytics can develop house file segmentation for retention and reduced churn, looking at lapsed customers or donors to identify the data profiles, timing inflection points and warning signs that trigger outreach and nurturing campaigns.

Optimizing for Channel and Product/Services Offer

Data analysis and modeling can also be used to improve future marketing ROI in terms of channel preferences and even product/services development. By studying customer or donor response and behavior after acquisition, analytics can identify the most appropriate promotion and response channels, communication types, and preferred contact timing by target audience. Plus, a customer model can match demographics, psychographics and behavior with product and offer choices to tailor prospecting, as well as upsell or cross-sell opportunities, to boost future results.

Committing to a Good, Clean Customer Database

Reliable predictions require a database of clean, updated existing customer or donor records, with enough necessary demographics/firmographcs and transactional behavior for modeling. So, to prevent garbage-in-garbage-out results, AccuList also supports clients with list hygiene and management, including hygiene matching for DO NOT MAIL, NCOA and more, data appending of variables from outside lists, merge-purge eliminating duplicates and faulty records, response tracking with match-back, and more advanced list screening options.

Targeted E-mail Expands Museums’ Direct Marketing Options

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While previous AccuList posts focused on direct mail strategies for our museum marketing clients, e-mail marketing is also an area where our expertise can help museums reach new members, event participants, or donors, as well as improve the performance of existing e-mail databases.

Study Museum E-mail Benchmarks and Success Stories

Evidence that e-mail can be a successful player in museums’ multi-channel campaigns comes from Constant Contact’s March 2019 e-mail statistics for house databases in the arts, culture and entertainment vertical (including museums and galleries), which show overall e-mail open rates averaging 17.54%, and click-through rates averaging 6.81% for the vertical. Those results are better than the all-industries averages of 16.74% open rate and 7.43% click-through rate, plus ahead of all but 13 of the 34 verticals tracked, and far ahead of some verticals, such as technology (e.g. web developers), automotive services, salons, retail and consulting. Marketers can also use e-mail to prospect for new members, donors and event participants. For example, marketers report success with event audience building via a series of e-mails that start with a promotion linked to ticket purchase, RSVP and/or social-sharing request, then follow up with reminders prior to the event, and finish with a post-event thanks e-mail that includes a request for an online review. Other successful e-mail series reward loyalty or re-engage dormant supporters by offering special perks (such as discounts). E-mail automation can make contact strategy even easier with programmed triggers, such as a re-engagement e-mail automatically sent six months after a last visit. For some creative inspiration, check out this nonprofit e-mail gallery and Pinterest grouping of museum e-mails.

Invest in Clean, Targeted E-mail Lists

Earning response to a house database or prospect list requires a few e-mail basics: 1) personalized, targeted messaging; 2) a brief subject line that inspires opens and engaging CAN SPAM-compliant creative content that inspires click-throughs; 3) mobile optimization of the e-mail with a clear call-to-action linked to a mobile-optimized digital landing page; and 4) an updated, clean opt-in e-mail list to avoid spam filters. As data experts, AccuList’s services especially focus on the last point. For responsive, targeted prospects, AccuList’s proprietary research has identified the top choices among opt-in e-mail rental lists (plus telemarketing and direct mail lists), including lists of museum members/donors, lists of museum mail-order buyers, and lists by type of museum and collection (download our free compilation of top list datacards). For clean, targeted house lists, AccuList points marketers toward database enhancement and hygiene, including identification of recent e-mail address changes through Electronic Change of Address (ECOA) lists, enhanced targeting by adding demographics from outside lists, and expanded e-mail reach by appending opt-in e-mails to postal records.

Pair Mobile-Optimized E-mail and Landing Pages

Every e-mail—regardless of target audience—needs a clear call-to-action linked to an online page that makes that action easy to accomplish. For fundraising e-mails, check out these best practices suggested by online fundraising software provider DonorBox: 1) include a prominent Donate Now button in the e-mail with a link to an online landing page, either one page for general donations or a page per specific project; 2) include suggested donation amounts on the landing page and tie those amounts to outcomes that show how they will improve the museum and visitors’ experiences; 3) optimize the e-mail and landing page for desktop computers, mobile phones and tablets; 4) include recurring giving options on the online page for higher donor retention; 5) if appropriate include a donation “thermometer” or other graphic of progress on the donation page to encourage more donations; 6) allow for multiple secure payment gateways, such as Apple Pay, Google Pay and PayPal in addition to credit cards; 7) and, finally, make sure the donation form and its processes are as simple, clear and quick as possible.

Combine Social Media Engagement With E-mail Targeting

E-mail can be a natural complement to social media campaigns, which is why social media networks themselves use e-mail marketing for customer retention. Museums can pair social media’s ability to engage and build brand, community and web traffic with e-mail’s advantage in delivering highly targeted and personalized messages, enhancing the power of both channels. Social media apps and forms can be used to capture new e-mail opt-in subscribers, for example. With platforms like Facebook, house e-mail data can be matched with the huge social audience to deliver demographics- and interest-targeted ads and promoted posts to existing names and lookalikes. Social media also is good at soliciting user-generated content (reviews, images, videos and posts), which can be used (with permission) in e-mails to boost response. And both social media and e-mail targets can be matched with direct mail for multi-channel power. Check out AccuList’s social media user lists, Facebook match and target options, and Digital2Direct programs combining direct mail with Facebook or e-mail lists.


Make Sure You Have a 2019 Data Hygiene Plan

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As marketers prepare to launch their 2019 campaigns, they should make sure that a complementary data hygiene plan is in place, and certainly AccuList USA data services stand ready to aid in ensuring the quality, up-to-date, enriched data essential for achieving marketing results.

Why Does Clean Data Matter?

Marketers don’t want to join the 88% of U.S. companies whose bottom lines are hurt by dirty data, based on Experian research. The top areas impacted by poor data practices are marketing (66% of companies) and lead generation (80% of companies), according to DemandGen. Dirty data leads to poor targeting and ROI for marketers, reduced revenue from customer acquisition and retention, wasted company resources and misdirected strategy. To avoid that fate, marketers need a plan to regularly fix any customer and prospect data that is incorrect, inaccurate, incomplete, incorrectly formatted, duplicated, or irrelevant, plus to enrich the database via appending of relevant but missing customer parameters.

Developing a Data Cleansing Strategy

Pete Thompson, founder of DataIsBeauty.com, has put together a useful primer for developing a data hygiene plan. Start with the basics: Decide what data is important for business decisions and estimate the ROI of data quality improvement. Then review existing data processes: types of data captured, where it comes from and how is it captured, the standards for data quality, how errors and issues are detected and resolved, etc. Other questions include the main sources of errors, methods for validating and standardizing data, methods for appending or combining multiple sources, automation used if any, accountability for data quality, and measurement of data ROI.

Key Elements of a Data Hygiene Plan

Without going into detail, the basic steps of the data plan will start with creating uniform data standards, preferably applied at the point of data capture. Then develop a data validation process, applied either when data is captured or, if that is not possible, at regular intervals for data already entered. After data has been standardized and validated, you can append missing fields by cross referencing with multiple data sources. Streamline the process through automation tools and scripts, saving time and money and reducing human errors. However, while it may be tempting to start with automation, Thompson cautions against putting the cart before the horse; success requires having data standards and a proven validation process in place before automating. And then set up a monitoring system of the hygiene process, whether automated or not, via random test samples and back testing, and implement periodic checks.

For regular monitoring, or overall scrubbing without an automated regimen, experts suggest a quarterly hygiene review for databases of 100,000 records or more, and semi-annual cleaning for smaller databases. Based on our own years in the data business, we think the best advice from Thompson and other experts is to enlist the services of data processing pros when hygiene is due!

Check out more details from Thompson’s data hygiene plan.




Many Business Publications Fail to Fully Mine Audience Data

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Business periodical marketers come to AccuList USA for help with audience building via multi-channel campaigns. But as data experts, we’d like to remind them that their audience data offers other revenue streams worth mining. Most publishers know that targeted audience data is key to competing for ad dollars; for improved subscriber response via personalization; and for better targeted content marketing, but a recent Adweek article by Jason Downie suggests several other ways to monetize audience data.

Building Valuable Off-the-Shelf Audience Segments

Downie urges publishers to build “off-the-shelf” audience segments that can be sold directly to advertisers, for example. Consider how a seminar promoter could use a business magazine’s data if the publication built an audience of people interested specifically in his topics or proven seminar buyers; the advertiser would be able to enjoy the benefits of tapping not just a business-engaged audience but a strategically targeted set of potential buyers more likely to convert. By creating off-the-shelf audience segments, the publication offers more options for ad clients and more targeted impressions from high-value users. Audience segments can also offer insights that can be further monetized. For example, analytics could show that seminar attendees are four times more likely to share content online. That makes them online influencers, and since influencers are extremely valuable, the publisher can demand a higher CPM. Additionally, an audience segment can open the door to new advertisers and marketers, including non-endemic spending. A business publisher’s analytics may show a subscriber segment visits golf sites as well as the magazine site, for example. The publisher can now woo clients looking to target “golfers.”

Using Data to Win RFPs

Another way publishers can take advantage of data is in the RFP process, according to the Adweek article, noting that the average publisher spends up to 1,600 hours per month, or 18% of revenue, responding to advertiser RFPs. Publishers can develop a customized response to an advertiser RFP, starting with first-party data to build out the RFP-requested audience and then enriching that database with third-party data appending. Digital campaigns can expand targeting by adding lookalikes. Author Downie advises running a portion of an ad campaign without audience or contextual targeting to identify additional audiences, interests, actions and behaviors of those who respond well to the campaign but were not included in the initial targeting.

Turning Data Into New Revenue Streams

Another option for publishers with high-quality audience data is to sell it as “second-party data.”  The data can be sold either directly to another company through a second-party data exchange or through a programmatic data exchange. Second-party exchanges are popular because they are private marketplaces one-to-one with another company, versus an open environment. And, of course, subscriber lists can be monetized as “third-party data,” earning regular rental revenue on the open market and via data brokers. For more detail, see the full article.

How Can Performing Arts Marketing Find the Best Targets?

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Since AccuList USA has successfully worked with performing arts and cultural organizations in audience development, supplying data and data services to help them acquire new patrons, ticket buyers and supporters, we were happy to see a recent npENGAGE.com post underscoring the key role of quality data targeting in performing arts marketing success.

Identify & Understand the Best Audience

Basically, performing arts marketers must acquire prospects with the potential to become long-term, high-value patrons; retain them; and maximize their dollar contributions. That challenge is not easy when studies show 72% of single-ticket buyers do not return, points out npENGAGE article author Chuck Turner, a senior analytics specialist at the Target Analytics agency for arts and cultural clients.  So a cost-effective marketing strategy will rely on data analytics both to target those with the highest relationship potential and to personalize messaging and offers for boosted ROI and loyalty.

Target to Increase Revenue & Donations

Analysis should look at the value of patrons in terms of the average of all revenue earned, including things such as gift shop and concession sales and tuition for classes offered, as well as ticket sales and subscriptions, Turner urges. That means targeting likely high-revenue prospects, plus, since it’s easier to increase revenue from existing patrons than to acquire new ones, targeting the right members of the audience pool for offers of add-ons and upgrades. For both groups, Turner suggests selecting those with higher average income, and thus higher capacity to spend. According to the Bureau of Labor Statistics, the average high-income person spends over $8,200 on entertainment each year, so if average program revenue per attendee is $34.33 (the average performing arts program revenue per attendee in 2013), there’s room to grab a bigger share! When it comes to increasing donations, external list data on both discretionary spending ability and nonprofit donation history can be used to target significant nonprofit donor prospects for acquisition, and that data can be appended to the existing audience database to better target for add-ons and upgrades. Turner points to Target Analytics findings that, on average, up to 40% of nonprofit audiences can be top prospects for significant contributory giving–if you communicate to prospects with a message that resonates with their mission-based interest.

Segment to Maximize Lifetime Value

With limited resources, performing arts marketers need to be more strategic and proactive in focusing on the most valuable segments. This means tracking lifetime value, defined as the net profit attributed to the entire future relationship discounted to its current value. Again, quality data can help target the right people–those with high lifetime value–with the right message. For both audience database and prospecting mailing lists, Turner stresses selecting targets based on charitable giving and income/discretionary spending ability. Conversely, knowing those unlikely to donate or spend helps minimize investment in unprofitable segments. For more, see https://npengage.com/nonprofit-fundraising/arts-fundraising-and-analytics/

Focus on E-mail Data for 2018 Insurance Marketing Success

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Success with e-mail in 2018 insurance marketing boils down to using quality, targeted data–something that AccuList USA is committed to delivering. Data provider V12Data summed it up well in a recent post offering basic insurance e-mail data tips.

Start With Clean, Up-to-Date Data

With an estimated 30% of e-mail subscribers changing their addresses each year, make sure all e-mail lists are up-to-date, with addresses validated and verified, including any e-mail addresses that have been matched and appended to a postal list. Good list hygiene should include removing duplicates; correcting formatting errors; identifying addresses known to be associated with spam traps; and eliminating hard bounces, invalid e-mails/domains, and e-mails associated with complaints.

Profile, Segment and Personalize

There’s no point to all that quality e-mail data if it’s not used to understand and target your audience. That means looking at both actionable internal data, such as customer service records, transactions, credit card purchases or e-mail responses as well as relevant demographic data, either from first-party collection or appended via third-party data aggregators. Consumer demographics could include date of birth, home ownership, occupation, gender, estimated income, age, presence of children, investments and more. Then segment your lists in order to offer the right product to the right audience segment. Plus use data to personalize offers and creative, and that means going beyond a Dear FirstName. Today’s e-mail audience expects and demands personalized offers.

Pay Attention to Buying Cycle and Life Cycle

Smart e-mail campaigns nurture customers and prospects through the buying cycle. Because those who request general information and those who fill out a request for quote form may be at different stages of the buying cycle, they need different messaging. Website signups can be sent a personalized welcome message, while subscribers who have not taken further action can get a follow-up nurturing message about products and services, with a call-to-action promoting a free quote or agent call. When a prospect makes a quote request, e-mail messaging can focus on getting to a policy sale, with more policy information and a specific offer or promotion. Note that life cycle counts as much as buying cycle. Consumers are more likely to buy insurance during major life-event changes, such as marriage, divorce, moving, home purchase, a new baby, retirement, etc.  Leveraging that data in targeting sends the right offer at the right time for maximum response.

Check out AccuList USA’s insurance marketing data expertise and clients on our website.