For 2020: Clean, Personalized, Predictive Data

As 2019 closes, marketers have a year's worth of multichannel customer, campaign and sales information to analyze for 2020 plans. So what are the big data trends that will maximize ROI? Clean, up-to-date, quality data is still the basis for effective marketing. So 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 data entry point. Next validate the accuracy of data via data tools or expert data services. Identify and scrub duplicates. Once data is standardized, validated and de-duped, improve its analytic value with third-party data appending. Establish a feedback process to spot and update/purge incorrect information, and communicate standards and processes so all teams understand the value of clean data in segmentation targeting, lead response, customer service, etc. Meanwhile, the 2019 Martech Conference highlighted other trends, such as the role of data in personalization. Expect to see increased use of Artificial Intelligence (AI) and machine learning (ML) for personalization. For example, for more personalized acquisition, ML can 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. When personalization is combined with elimination of data silos and creation of a single customer view across channels, marketing becomes especially powerful. Indeed, data integration and elimination of data silos are key to the growing "agile marketing" trend, which breaks down team silos to focus on high-value projects collectively. Marketers should also boost use of predictive modeling. 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, it’s not as good at informing future multichannel directions. Standard data analysis often mistakenly gives most credit to last-click channels such as search or transactional activities. The Keen/ClickZ survey found marketers using predictive modeling boosted results in multiple areas, including better understanding of the target audience (71%), optimizing touchpoints on the customer journey (53%), and improving creative performance (44%). For more detail, see https://www.acculist.com/prep-for-2020-marketing-with-clean-personalized-predictive-data/

How Data Silos Spoil Marketing Harvests

Silos can be great for agricultural storage, but they spell trouble when we're talking about customer data trapped in company departmental and systems silos. Research shows the magnitude of the problem. For example, a recent blog post by Veriday, a digital marketing company, noted that more than 80% of marketers say data silos within marketing obscure a seamless view of campaigns and customers. And that doesn't even consider data trapped outside marketing in IT, sales, etc. In larger, older companies, many data silos result when outdated processes and separate information systems hamper linkages. Yet silos are not just a big-business issue given the average small business today is using 14.3 different systems, as the Veriday post points out. Yes, information can be transferred between silos via import/export or manual efforts, but this risks duplication, errors, delays, inconsistent hygiene and inaccurate updating--meaning poor immediate ROI and wasted future opportunities from an incomplete and inaccurate picture of customers, campaigns and channel results. In business-to-consumer marketing, data silo risks are growing more acute, stresses a Forbes magazine article by Denise Persson, CMO at Snowflake, a data warehouse firm. She cites Accenture survey results showing that, while the promise of a deal or discount was the top driver of customer loyalty last year, in 2017, 58% of customers find marketing programs that are highly tailored to their needs much more enticing. Marketers can embrace targeted, contextual approaches, but, Persson warns, if each marketing channel--website, social media, e-mail, online ads, direct mail--uses a different set of data to develop a different channel strategy, marketers will end up with a fragmented customer picture delivering a fragmented brand experience! Smart marketers will invest in solutions, such as third-party support, software for content management and marketing automation, and data warehousing. Meanwhile, a blog post by Ajay Gupta, founder of Stirista, a digital marketing agency, points out the myopia of failing to link business and consumer data, especially now that digital media is blurring the line between professional and personal lives. Gupta gives the example of a company that wants to market a personal electronic device by targeting a proven business prospect list with only B2B e-mail addresses. If the company enhances the prospects' B2B info with B2C data, it could expand its reach by sending out e-mails to B2C addresses, direct mail to home addresses, online display ads via digital cookies, plus targeted social media ads! Linking B2B and B2C data is also a great tool for onboarding and creating social media custom audiences, per Gupta. For more detail, see http://www.acculistusa.com/how-b2b-and-b2c-data-silos-spoil-marketing-harvests/