Survey finds marketers struggle to deliver personalized content
MarketingCharts staff
Through a special arrangement, presented here for discussion is a summary of articles from MarketingCharts, which provides up-to-the-minute data and research to marketers.
Delivering personalized content is the most challenging barrier to marketing automation success, although the integration of all marketing systems is a close second, according to a new report from Ascend2. Despite the difficulties marketers are having delivering personalized content, the vast majority say that content personalization driven by marketing automation is improving.
The survey was fielded among 250 marketers worldwide, who were fairly evenly split between a B2B (40 percent) and B2C (33 percent) focus, with the remaining 27 percent targeting B2B and B2C equally.
The delivery of personalized content is one of the top priorities for marketing automation optimization, per the report, though it falls behind more general goals such as creating a successful strategy and improving the user experience.
The survey presented respondents with a list of seven tactics used to optimize marketing automation, asking which were among the most effective and the most difficult to execute.
The tactic identified as effective by the largest share of respondents was customer experience mapping (53 percent). Customer journey mapping has been seen as a top practice in boosting conversion rates for enterprise B2B marketers and is a distinctive trait of top-performing marketers.
Close behind customer experience mapping is personalized/dynamic content, noted as effective by 51 percent of respondents. These two tactics are considered effective by a wider swathe of respondents than others, such as landing page and form CTAs (35 percent), AI and predictive modeling (34 percent) and A/B or multivariate testing (28 percent).
The relatively low level of perceived effectiveness for AI and predictive modeling is curious given other research indicating strong enthusiasm surrounding its use. It may be that marketers simply don’t have much experience in this area.
AI and predictive modeling emerged as one of the most difficult tactics used to optimize marketing automation. Cited by 45 percent as a difficult tactic, it was narrowly behind only one other: personalized/dynamic content (46 percent).
- Which Tactics Are Proving Helpful in Optimizing Marketing Automation? – MarketingCharts
- Optimizing Marketing Automation – Ascend2
- B2B Content Marketing Is Becoming More Audience-Focused. Or Is It? – MarketingCharts
- Two-Thirds of B2B Marketers Are Testing Content Personalization – MarketingCharts
- B2B Marketers Say Email Delivers the Highest ROI Leads – MarketingCharts
- Are Current Marketing Technologies Supporting the Optimal Use of Audience Data? – MarketingCharts
- Few B2B Marketers Report Using More Sophisticated MarTech Features – MarketingCharts
BrainTrust
Charles Dimov
Vice President of Marketing, OrderDynamics
Susan Viamari
Vice President, Thought Leadership, IRI
Ian Percy
President, The Ian Percy Corporation
Discussion Questions
DISCUSSION QUESTIONS: Where do you see the pain points in executing marketing automation? How do you see the technology evolving? How would you rate marketing automation’s benefits and its shortcomings?
Marketing automation is necessary, but not sufficient for personalized content. The headline for this discussion focused on personalizing content. The pain points are many. In order to personalize, the ground zero assumption is that you have CRM that can identify the individual at the moment they engage, where they engage. Assuming that you can identify the individual, there must be rich content that the customer deems relevant. Increasingly, the customer wants content choices, and choices on how they view it.
The overall challenge is that many retailers are still stuck in a world of delivering mass content customized by segment. A recent survey found that today’s customers want to control 85 percent of their own experience, including personalized choices and content. The number one issue and pain point is that retailers have to rapidly transform the paradigms, infrastructure and content to enable individuals to both engage and drive their own experience.
I completely agree with Chris. The level of personalization that consumers are looking for is not matched by many retailers and companies. Companies need to redefine personalized content, experience and product solutions in order to better meet consumers’ expectations.
The toughest part is organizational focus. Change management demands time and energies that are usually already accounted for and committed, so even though the desire for improvement exists, it has to compete for resourcing and attention. Marketing automation has suffered because it has distinguished itself as an art, where it is being quickly proven to be a science. The transition is occurring but with the huge opportunity costs inherent in unrealized benefits because of the slow pace.
For marketers, MA is great. But the challenges we are seeing are that the customers and prospects see through light automated personalization attempts. It works for the mass mailers and drip campaigns, but we are not there yet in terms of having that 1:1 feeling.
There is continued talk about AI in marketing. Very exciting — IF you have enough data. In B2C this can have a huge impact. There is still a long way to go on the B2B side, where data is not as plentiful. Will marketing AI’s application make enough sense to pay for the costs of implementing these systems? Of the various vendors who have pitched me, I have yet to see a believable and compelling ROI.
Not to be a downer. The tech is very interesting and shows promise. However, we are clearly early in the journey. Where AI vendors need to concentrate is on how to eek out training the engine to pick out solid prospects/targets — when you don’t have millions of data points.
There is a plethora of enabling technologies in the marketplace that can help with various aspects of marketing automation which creates the issue of deciding the most significant ones that can impact individual businesses. For example, A/B testing which is 28 percent effective in the survey and 30 percent more difficult can be easier to implement with companies like Market Dial. Or measuring in-store shopping behavior can be less difficult with a company like RetailNext (note: I am a technical fellow at this company).
The pain point for brands and retailers is to figure out which enabling technologies across all functions would best align with the over-reaching strategies of the company. The IT roadmaps need to be carefully planned to support all functions with a synergistic approach inclusive of marketing, operations, merchandising and human resources.
The initial pain point for marketing automation software is often the financial investment and business justification for it. When you effectively leverage SaaS solutions, they can deliver engaging customer journeys across email, mobile push, SMS and social with AI-powered marketing automation at a very attractive TCO (Total Cost of Ownership). With the intensely-competitive market currently, I see even more value and functionality evolving to the benefit of the corporate buyers and end users.
Am I alone in thinking that just maybe marketers are trying too hard? We’ve hit a point where we need a dictionary just to understand marketing jargon; a sure predictor of eventual demise. My goodness, how does using “automation” and “personalization” in the same sentence make any real human sense? Complicating a process is also often just a way to escape brutal truth … we’ve got to get back to human basics of heart-to-heart communication. Not everyone wants our stuff no matter how we try to personalize it. If we can’t do well by putting out a genuine, appealing, persuasive story perhaps we’ve got the wrong stuff.
Traditional business practices can limit the scope of personalization efforts and often won’t allow a holistic approach to understanding consumers and marketing to them. And they don’t consider enough what the modern retail landscape and consumers really look like. But technology is evolving at the speed of light, including artificial intelligence and machine learning, which are the next evolution in how we interact in the digital world. These tools offer new ways to attract and retain consumers.
Perhaps the most challenging obstacle for marketers is the reams of disparate — and often discordant — data swarming and always growing throughout the marketplace. There is a need for real-time access to fully integrated — and harmonized — data. While this has been prohibitively expensive and time-consuming in the past, this is no longer the case. These harmonized data sets alleviate the need for manual efforts and they significantly increase speed to insights. Further, integrated data provide a more efficient link between market demand and actual market behavior, keeping users aligned against category-focused/customer-first efforts.
Automation and personalisation seem like the opposites of each other! That’s not to say that you can’t use automation to deliver personalisation as it’s obviously not really feasible for a huge retailer to personally write emails to each customer. But personalisation always carries an element of authenticity and mass-emails are always easy to spot. Finding a sweet spot between something that feels real enough to the customer and actually targets them as an individual, and being able to do that on a mass scale is the challenge for marketers and tech.
One of the biggest pain points is the disconnect (or void) between brand marketers and retailers. The term “marketers” can of course be applied to both retailers and brands but it makes sense to separate the two particularly when it comes to content. Retailers wanted brand marketers to step up and create multi-touchpoint content plans that took retailers’ goals and preferred platforms into consideration. Some brand marketers have forfeited that opportunity, resulting in the latest example of “if you want something done right …” on the part of retailers. Multi-stakeholder goals should be ironed out before multi-tech solutions are put into place.