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• Voice technology is being widely adopted, thanks to the global distribution of voice assistants like Google Assistant, which is installed in over 1 billion devices as of 2020.
• Improvement in voice recognition accuracy is also helping with widespread adoption of voice technology. Google achieved a 95% accuracy rate for the English language as of March 2017. This is the same threshold for human accuracy.
• 82% of consumers expect an immediate response on sales or marketing. Voice recognition technology, which enables the immediacy of customer service responses, is addressing this need for many businesses.
• Voice-enabled tools are increasingly being employed within an organization’s martech stack, to facilitate internal operations. Examples include speech-to-text transcription tools, real-time conversational analysis, and automated call listening/conversational analysis platforms.

WOM Protocol, a next-gen MarTech solution that enables brands to leverage word-of-mouth recommendations, has just announced that its native WOM Token is now listed on the Liquid cryptocurrency exchange. This listing represents the fourth top-tier exchange listing for the WOM Token and the first WOM/BTC pairing.

The WOM Protocol, together with the WOM Token, provide a way to reward creators without compromising consumer trust in the content and its creators. The WOM Protocol will become the main marketing channel for brands, targeting the $335 billion annual digital marketing spend, and the main revenue stream for content platforms.

Given the above, it’s not surprising that the primary no code use case reported in our survey was implementing workflows and processes (82%), often across multiple apps and platforms within a martech stack. Next most popular, but significantly lower at 37% and 35%, were publishing web forms and setting up databases. Essentially: collecting, routing, and storing data.

In looking at a lot of different no code tools — and there are a lot of no code tools out there now — I noticed that many fell into one of three “patterns” of how they worked:

Design & Content (UI) — web and mobile app builders, bot flows, interactive content
Spreadsheets (Data) — if you can use Excel or Google Sheets, you can build an app
Automation (Logic) — workflow and integrations (iPaaS) with event-driven models