Vendors of these low- and no-code development platforms promise marketers they can help with analytics, data science and machine learning. These come in the form of simple dashboards to rather sophisticated predictive analytics with products such as Oribi, Gyana, Onna, Lido, Obviously.ai, etc., according to according to Scott Brinker, author of the Chief Marketing Technologist blog.
“The data science stuff is really interesting,” Brinker said in an interview with CMSWire. "We've got so much data, but data scientists are expensive, and when we do get them we have a stack of things 10-feet high that we want them to do first. But this is another good example where machine learning is being applied” with low- and no-code platforms.
Marketing Tasks, Gone By Wayside, Return
Brinker's so bullish on the impact of these low- and no-code platforms on marketers it was the topic of his keynote earlier this year at the MarTech Conference. Marketers would never even bothered with certain tasks related to data because a data scientist’s waiting queue is never-ending. Until now.
“It’s such a simple little thing, but I do want to get the answer, and so now if I have a tool that sort of lets me answer those quick and simple low-end cases,” Brinker said. “I mean these are things that basically we were leaving on the table. They just weren't getting done at all because it wasn't economically feasible to do them.”
Low-code machine learning allows development to be done in a democratized way, allowing the rapid deployment of a customized tool designed directly by a marketer, keyed to the needs of the consumer, according to Ben Smith, senior development consultant at Quandary Consulting Group.
"Similarly, analytics in a low-code scenario allows a marketer to quickly deploy tools to assist in consuming and understanding data, which in turn, allows for a faster understanding of current market climates," Smith added. "Then, the marketer can make rapid decisions based on that data, moving to implement new tactics based on a high-level understanding of the market. With the right low-code tools, such analysis can be done on demand, in a repeatable fashion, painting an up-to-date state of the market."
Avoiding 'Technical Malpractice'
No platform just emerges into the marketing stack and is beautiful and seamless right off the bat and forever there on out, though. Marketers still need to ask hard questions about implementation and integration realties.
And of course there are the developers, the bedrock of all things software for many organizations and marketing teams. How do they fit into the low- and no-code scheme of the marketing stack? Is there a developer mistrust of these tools? Are developers worried for their jobs?
“I don't have a mistrust so much as thinking there's likely a mismatch between the hype and what the technology can deliver,” said Ryan Bennett, technical architect and co-founder of Cylogy, a San Francisco-based Sitecore and Episerver consultancy. “I mean, at the low-end you have systems like Wordpress where, as long as you don't have highly-customized needs, you can build a fully functional site with many features, without needing to code."
Moving up to mid-level and enterprise software? You see the same drivers: a focus on component-based visual development with varying levels of sophistication and completeness and cloud-based services that allow companies to offload complex work. "All of that is good," he said.
However, where Bennett thinks the “slogans hit reality is if you're traveling off the beaten path.” Case in point: if you have custom needs or requirements, you're probably going to need some coding.
“Moving forward,” Bennett said, “I think these systems and tools make it so that having developers working on basic functionality is a form of technical malpractice. It is already becoming a thing of the past. In most projects we'll see low-code/no-code functionality used to build out big chunks of projects — the majority of functionality — with developers working on the 10%/20%/30% of app/site functionality that fills custom needs and that low-code/no-code solutions would have a hard time solving.”
For most organizations, low-code will never get you all the way there, Laurence Hart wrote in a CMSWire article. "It may be able to knock out a task or get one started," he added, "but doing it all can be tough. While most processes are common from a high-level perspective, it is in the nitty gritty details that the commonalities break down."
Where Natural Language Processing Appears
Rich Waldron, CEO and co-founder of Tray.io, a platform cited by Brinker in the IPaaS/integration arena of low- and no-code platforms, said marketers with low- and co-code platforms have incorporated data science into their channel marketing and messaging programs by way of including NLP (natural language processing) into their website chat tools to field specific product questions from leads.
Marketers use low-code automation tools to configure their existing website chat tools with an NLP-based approach which, in the simplest cases, can recognize common re-phrasings/acronyms/misspellings of keywords. For instance, “I need help with my salesforce CRM,” or “Does your company support SFDC?”
“We’ve also seen some marketers use the... custom logic operators in low-code automation platforms to create fully customized, NLP-driven customer journeys entirely based in chat that branch into different, context-sensitive areas depending on the keywords that leads include with their queries,” Waldron said. “We’ve seen marketers thoughtfully combine NLP modeling, their existing chat tools and low-code automation.”
Related Article: Is Low-Code Technology Right for You?
Generating Full-Funnel Analytics
Waldron added marketers face challenges in absorbing, centralizing, aggregating and analyzing marketing data at large. They’ve relied too heavily for reporting on IT and BI support for data management issues, and hours of manual work for everything else.
“Marketers are increasingly adopting low-code tools so they can connect their different marketing tools and channel data, and build out custom processes, such as reporting, all by themselves,” Waldron said. “Low-code tools help marketers easily integrate multiple data sources and flow the data into a centralized location, such as a data warehouse. Afterwards, teams can layer business intelligence tools onto their data warehouse to generate full-funnel analytics for every single channel.”
In the presence of a low-code environment, data science will shift to move the analytics directly into the hands of the marketer, in effect making them the data scientist, according to Smith. Such "marketer-scientists" will then move forward becoming ever more specialized, as they seek to add value to the business. "Rather than being replaced by AI," Smith said, "their creativity, insight, intuition and all the other things that make a human being unique will be even more in demand."
'Doing the Thinking for You'
Brinker cited a tool like obviously.ai that’s built in much of the pattern detection in machine learning that marketers have to connect to marketing platforms and then can start to analyze patterns like churn.
AI supporting these tools is becoming much more sophisticated, Brinker said, citing a platform like Canva. “I'm not a graphic designer, but I can use things like Canva because Canva has now started to implement this level of machine learning that actually helps create patterns for you,” Brinker said. “It's doing the thinking for you, and it's doing some of the suggestions for it. I mean, it's not going to create something completely net new. You still do need graphic designers in the world, but for a whole bunch of these use cases it would be a waste of a graphic designer's talent."
IPaaS Integration Engine at Play
Many of these low- and no-code platforms help marketers connect to different sources of data, Brinker said. They’re not only good at the actual analysis piece of determining data trends and fostering experimentation with predictive analytics.
“It's that underneath,” Brinker added, “most of these tools have almost like an IPaaS-like integration (Integration Platform as a Service) engine that says, ‘OK, I can connect to all the different sources of data that I have.’ And some of those sources of data are well-established platforms. But so many companies, they have a ton of data that isn't even residing in a specific martech platform. It's data that they're collecting through maybe their own custom software and all these other sources that feed into it.”
That’s where some of the low- and no-code data science platforms can connect to all the data from different sources and bring that together in a mode where you don't have to be a database architect or data warehouse specialist. “You're now able to do this layer of exploration and analysis on top of that,” Brinker said, “where before it just wasn't accessible to most people.”
Brinker also cited the Airtable app, which helps marketers organize operational data between things like tasks, projects and campaigns.
Related Article: A Look at Marketing's Biggest Data Challenges of the 2020s, Part 2
'Game-Changing' Marketing Transformation
Stepping back to the big picture of where these surging low-code and no-code platforms fit into the marketing operations scheme, marketers can think of these platforms for many use cases and overall into three main buckets: automation, augmentation and integration, according to Brinker.
“What we think of as digital marketing continues to sort of grow in scope,” Brinker said. “It's not just static assets. Everything is increasingly having some sort of app-based logic, whether it's app-based logic a customer directly engages with or something happening behind the scenes that is prospects and customers doing stuff. And we want to trigger all sorts of interesting activities within the organization to respond. That's expanding.”
Furthermore, instead of bottlenecking all of that work through the overworked IT department, and even the overworked marketing ops department, many no-code and low-code tools are popping up for a steadily larger set of marketing operations use cases, according to Brinker.
“A regular marketer can actually make these things happen themselves,” Brinker said. “They don’t need IT. These capabilities are now starting to be in the hands of the general purpose marketer. I really do think it's like a game-changing transformation of the field.”
Mobile App Builds, Landing Pages
So where else specifically is the game changing outside of analytics, data science and machine learning? Brinker wrote in his blog he finds the augmentation category of no-code platforms the most fascinating for marketers:
- Web and mobile app builders: Create fully functional web apps or even native mobile apps without knowing any programming language, purely visual creation — products such as Bubble, Glide, Adalo, Parabola, etc.
- Spreadsheets, databases and superdocs: Create database apps and project experience with products such as Airtable, Notion, Rows (formerly DashDash), Smartsheet, etc.
- Bots, voice and virtual assistants: From website chatbots to Alexa skills, create conversational experiences for customers without code — products such as FlowXO, Chatfuel, Voiceflow, Exceed.ai, etc
- Creative asset generation: Be creative without being a pro “creative” (i.e., a professional designer, video engineer, copywriter) — products such as Canva, Descript, Snazzy, Beautiful.ai, Bannerbear, etc.
Small Visual Changes Lead to Big Results
Ashley Stepien, the VP of marketing for Webflow, one of the platforms cited by Brinker in the category of websites, ecommerce and landing pages, said marketing initiatives have historically been one-sided: You put your billboard, poster, or other ads out into the world based on what you think will resonate with your audience, and you wait and hope those efforts turn into sales or conversions.
“The era of waiting and hoping is coming to an end thanks to low- and no-code tools,” Stepien said. “You can use real-time data to turn marketing initiatives into two-way conversations. The real-time marketing benefits that come from low- and no-code tools help teams think about growth from multiple angles in a more holistic way. Instead of just completely redoing image layouts or adding whole pages, teams learn to look for smaller changes, like shifting a call-to-action box or tweaking language.”
She cited an incremental adjustment her team recently tested out that involved overlay opacity. The team hypothesized that the background behind one of its CTA boxes was too distracting, thus reducing conversions.
“For a small sample of viewers, we eliminated the background noise and then monitored responses to this small adjustment for several days,” Stepien said. “This small shift produced statistically significant results — and actionable insights on small visual changes we could make to create a clearer user experience.”