Engineering as Marketing with AI
An underutilized marketing channel with new potential.
I’m always fascinated how Startups gain traction and build a user base. There are a lot of things big companies can learn from how startups do their marketing and grow their users. In the real early stages, startups may not have marketing people or big advertising budgets. In Traction: A Startup Guide to Getting Customers, the author talks about 19 traction channels a startup could implement to help bring in new users. One channel that stood out for me is Engineering as Marketing.
So what is Engineering as Marketing?
Engineering As Marketing is the practice of using engineering resources to develop complementary tools, products or services that provide value to your current target audience and helps promote or demonstrate your main product or company.
Examples of this would be evaluation tools, pricing calculators, embeddable widgets, simple apps and micro-sites that act as another potential acquisition funnel.
Key elements of Engineering as Marketing
- What you develop is complementary to your core product.
- It focuses on doing one thing well. Be low friction and be simple to understand.
- It should provide some sort of added value to your target user.
- It is typically free for the user to use but can also require exchange for their contact details.
- More value and utility for your current and target audience.
- Long term return and value for your business.
- Increased brand awareness and potential new PR push.
- Potential SEO benefits if it lives on another domain.
Adding in Artificial Intelligence
Implementing AI into your core product may take a little more time but creating smaller complementary tools and apps is the perfect way to experiment with AI. This allows companies to test if your target audience would find value from its use.
One key benefit of AI, is that Artificial Intelligence has the ability to make a users experience more personalized and tailored. AI tools such as IBM Watson Personality Insights and Microsoft Emotion Detection can provide a company information they typically wouldn’t be able to gain in the past.
Examples of tools created utilizing AI to make a users experience more personal are:
The North Face used AI to create a personal shopper that can help you find the perfect jacket for your next adventure.
TD Ameritrade created a tool named Alvi. The tool would first learn about you and then provide you with educational investing information based from what it’s learned.
Microsoft does a nice job of demonstrating their AI services by creating a gallery of micro tools and apps that use those services. Some examples include:
- How-Old.net: Demonstrating their facial detection service
- Fetch: A tool that recognizes dog breeds, demonstrating their computer vision service.
- CaptionBot: A bot that describes what it sees in images, demonstrating their computer vision, emotion and bing image search service.
Rise of the Bots
Bots are becoming more mainstream. This is due to the advances in AI and specifically, natural language processing. Bots are the perfect example of creating an AI powered complementary service that provides more value to your user.
We see a lot of major companies releasing a bot. Some examples are:
- Bank of America: A bot named Erica who makes suggestions for improving your financial affairs
- Whole Foods: Recipe finder bot
- CNN: Top news stories bot
- The Weather Channel: Weather update bot
Engineering as Marketing can be extremely valuable but typically may not be the easiest form of marketing to implement. With this said, the right tool could provide long term ROI to your core product. Now with Artificial Intelligence, there are amazing opportunities for new tools that would provide more value and show your audience how your business is innovating. The best tools are single-purpose low friction tools that solve obvious pain points.
This is the perfect space for technically strong agencies to play since Engineering as Marketing is an area in which the product team may not have time to test and the marketing team doesn’t have the engineering power to execute.
This year we will see a lot more AI-powered marketing tools that provide additional value to the user and aims to show innovation for that product or brand.
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