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A July 2019 Seismic-commissioned study (registration required) conducted by Forrester Consulting found only one in five organizations are effective at personalizing content at-scale, despite personalization being the top success factor for customer and prospect engagement. In spite of significant investment in the effort, personalization efforts still often fail. Marketing experts cite several reasons for this failure.
Failure to Connect the Personalization Dots
Gartner’s 2018-2019 CMO Spend Survey showed 14% of marketing budget is going toward personalization. Yet 74% of the 60 organizations surveyed in its 2018 State of Personalization Survey said they are struggling to scale their personalization efforts.
Jennifer Polk, VP analyst at Gartner, said while data is key component of personalization, marketing leaders are still learning to thread the needle between gathering and using data to deliver personalized and relevant interactions and understanding consumer attitudes to privacy, managing consumer consent to use their data and implementing policies and practices to respect both.
“Digital commerce is the leading use case for personalization, with more personalization engine users focused on digital commerce outcomes than marketing or CX personalization,” Polk added.
“Buyers have come to expect highly-personalized, valuable interactions with brands, and B2B companies that haven’t yet woken up to this are jeopardizing revenue,” added Doug Winter, CEO and co-founder of Seismic. “Today’s leaders are under pressure to implement mature sales enablement programs that allow sellers to close the gap between what the modern buyer expects, and what sellers are able to deliver. Asset personalization has proven to be a critical way for businesses to add value to each buyer interaction, strengthen relationships, and grow revenue as a result.”
Related Article: Which of the 3 Personalization Types Are You?
Lack of a Unified View of the Customer
“Many companies lack the capabilities needed to deliver the personalized, connected experiences their consumers want,” said Chris Jacob, director of product marketing for Salesforce Marketing Cloud.
Organizations need a unified customer view to deliver such a personalized experience, he added. However, according to 4,100 global marketing leaders in Forrester’s State of Marketing report, only 30% are satisfied with their ability to use data to create more relevant experiences.
“As it relates to sales and marketing alignment, we are definitely in the midst of an ongoing evolution, that has seen a lot of progress in recent years, but also a lot of challenges still ahead,” Jacob said. “According to our State of Marketing research, in 2018, 52% of sales and marketing teams share goals and metrics, and 54% are empowered to collaborate. This is an 86% and 87% year over year growth rate respectively. In other words, a slight majority of global teams across industries and business sizes are working towards common KPIs.”
Yet, at a tactical level this falls away, with only 45% of marketing and sales teams jointly executing on account-based marketing (ABM) programs. Ultimately this would result in a disjointed experience for a majority of business buyers with the brand which ultimately would mean lost sales, according to Jacob.
Related Article: How a Unified Customer Identity Supports Digital Experience
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Lack of Dynamic Content
"Making personalization work at scale requires machines that can understand and model the inherent complexity, and “dynamic” content that is created in real-time, by a machine, for a particular scenario within the personalization matrix,” said Jason Michaels, a managing director at Accenture Interactive. “Dynamic content can include customized headlines, messages, and images that are modified based on historical data. Humans help devise the models and provide seed content, which machines then use to create a new level of personalization at scale. Major strategic investments by Adobe and Salesforce in machine-driven personalization technologies are a strong indicator that the industry’s future lies in this direction.”
Related Article: Headless, Static or Dynamic Content Delivery? Try 'All of the Above'
Lingering Data Siloes
“Enterprises are seeking to become more effective at personalizing content at scale. Sounds good on paper. Here is what that means to a data engineer — 'get the ERP, MRP, CRM, marketing automation, web analytics, call center platforms and other IT-controlled systems all talking to each other, and then integrate predictive AI,'" said Chris Bergh, CEO of DataKitchen, Inc. "Typically, none of these systems interoperate. They are implemented in a variety of databases and on different software platforms. They utilize numerous programming interfaces and technologies. Manipulating all of this data is a daunting task requiring such a wide range of skills that it is rare to find a single person who can do it all.”
"The enormity of this task can only be truly appreciated when you understand how modern enterprises typically conduct data-analytics. Data engineers spend 75% of their time massaging data, executing manual processes and scrambling to respond to data errors. There is hardly any time left to create new analytics, let alone manually implement a massive data integration. When data remains locked away in isolation, it can’t be used to serve customers or the enterprise’s goals."
Related Article: Old MacDonald Met a Data Silo, E-I-E-I-O
Lack of Outreach
Personalization efforts are falling short across enterprise sales because organizations are failing to make personable outreach at the point of contact, according to James Ontra, the CEO and co-founder of Shufflrr. “Data insight providers are able to offer all kinds of ‘personalized’ details like who clicked what, when and how many times. This level of insight provides us with enough 'personalized' information to at least get an idea of who may be interested in your product or service — you know X amount of people from Y company ended up on page Z of your website. Once you wean down who the targets are, the real value comes when you’re able to leverage that data and make a real, one-on-one connection.”
For example, Ontra added, if you’re targeting large banks for your enterprise software technology and notice that four people from Wells Fargo have visited your product page in the past month, it may be worthwhile to go to a relevant industry conference the company sponsors to get some face time with them. To effectively leverage personalization efforts, the key is to first use data insights to pinpoint the appropriate target, and then identify the exact need.
