Artificial intelligence is all about data. Marketers need plenty of it at high levels of quality if they want to use AI tools. Some tools have access to data already, so marketers don’t need to provide it. But many solutions need data from a brand to get started—and this is where marketers run into trouble.
See, most companies have data, but it’s not all in a format that AI can readily use. For instance, a company might have tons of product images. An AI system could potentially analyze which of these images compel people to buy more product, but the images would need to be appropriately tagged. Tagging thousands or millions of images is a prohibitively expensive and lengthy process.
This is where Alegion (@Alegion) comes in. The company provides a workforce that is able to assemble AI training data and scoring at scale. Using a crowdsourced workforce from services like Amazon’s Mechanical Turk, Alegion builds large-scale, custom datasets that brands then use to train AI algorithms.
Publisher Conde Nast has used Alegion to tag images in hours instead of the weeks it used to take. Charles Schwab leaned on the company to process thousands of social media messages per day. These datasets were then used to teach AI systems to produce superior marketing results. In some cases, that might include predicting what content will work best based on past data. In others, AI may be able to surface sales insights from data that human marketers can’t
We sat down with Alegion CEO Nathaniel Gates to learn how the company helps brands get their data ready for AI.
In a single sentence or statement, describe Alegion.
Alegion provides cloud labor solutions of unlimited scale to process large volumes of data-intensive tasks, such as AI training data assembly and scoring, and user-generated content management.
How does Alegion use artificial intelligence (i.e. machine learning, natural language generation, natural language processing, deep learning, etc.)?
Alegion focuses on enabling AI and machine learning initiatives. The Alegion platform provides human-in-the-loop technology designed to create structured data for AI and machine learning projects.
What do you see as the limitations of artificial intelligence as it exists today?
Artificial Intelligence is only as good as the data used to train it. Alegion and a few other companies address the common challenges of building large-scale, custom-training data sets. Traditional approaches require a tremendous amount of human subjectivity to manually build, process and score high volumes of training tasks.
What do you see as the future potential of artificial intelligence in marketing and sales?
Artificial intelligence will be used to expedite customer transactions, increasing customer satisfaction. It will also be used to guide the customer on a journey that is mutually satisfying to the buyer and seller.
What makes Alegion different from competing or traditional solutions?
Alegion’s cloud labor solutions distribute transactional work to crowdsourcing marketplaces, such as Amazon’s Mechanical Turk, for fulfillment. This unique workforce solution provides exceptional data quality, predictable linear pricing and unlimited scale to process large volumes of data intensive tasks. Alegion manages each worker creating groupings by skill, geography, or performance. We have pre-curated groups for common tasks such as photo moderation or image tagging. Also, we can curate a custom group that is specifically trained and qualified to do your tasks at any scale.
Who are your prototype customers in terms of company size and industries?
Our customers range from enterprises to small, disruptive companies to the public sector.
What are the primary use cases of Alegion for marketing and sales professionals?
There are three use cases that easily come to mind: 1) finding sales opportunities, 2) formatting, combining and standardizing data for marketing use and 3) appending data to make it actionable.
Any other thoughts on AI in marketing, or advice for marketers who are just starting to explore the possibilities of AI?
AI is only as good as the data. Making sure the data a marketer has is actionable, relevant and drives to conversion is key to success.
Paul Roetzer is founder and CEO of Marketing AI Institute. He is the author of Marketing Artificial Intelligence (Matt Holt Books, 2022) The Marketing Performance Blueprint (Wiley, 2014) and The Marketing Agency Blueprint (Wiley, 2012); and creator of the Marketing AI Conference (MAICON).