Seeker’s very own MD Gareth Simpson offered this presentation on the power of machine learning and outreach. He shared sharing how the Seeker team scales outreach activities, allowing us to have more conversations with the right people, and ultimately win more links.
- Speaker: Gareth Simpson
- Job role and company: Founder & Managing Director, Seeker Digital
- Twitter profile: @simpsongareth
- LinkedIn profile: https://www.linkedin.com/in/simpsongareth/
- Link to the slides: https://www.slideshare.net/GarethSimpson2/lmfao-leveraging-machines-for-awesome-outreach-141771290
What was the talk about?
Gareth talked us through how to use machine learning (ML) to improve the outreach lifecycle. By using the bots to do the heavy lifting (without sacrificing the human elements of outreach) it’s simple to increase efficiency, have more conversations with the right people and win more links.
"Machine learning can be used to create more meaningful work and help you scale outreach campaigns without compromising human relationships" says @SimpsonGareth #brightonSEO pic.twitter.com/Fkg3ZKQ4gx
— Seeker Digital (@SeekerDigital) April 12, 2019
First, Gareth explained how ML fits into the complex web of artificial intelligence (AI). Ultimately, it can:
- Classify data
- Perform tasks without instruction
- Improve its own performance
- Automate and scale repetitive tasks
- Emulate human decision
- Classify content and production
Now that’s savvy robotics.
Then, we took a deep dive into the outreach process and how ML can help us reach new heights. Features include:
- Keyword research
- Ranking projections
- Intelligent prospecting
- Pitch optimisation
“Machine learning can be used to create more meaningful work and help you scale outreach campaigns without compromising human relationships.”
Interesting talk by Gareth Simpson at @SeekerDigital about leveraging machines for outreach, automating laborious manual actions like copy + paste and identifying key #journorequests more efficiently for more links #BrightonSEO pic.twitter.com/dqDdZhAxRo
— twentysix (@26digital) April 12, 2019
Potential impact on the industry
Outreach is hard – it’s no wonder both Kat Kynes and Shannon McGuirk discussed campaign fails at this April’s conference. It’s clear that to win links we need to get niche, accurate, and personal. But is that really scalable? With ML it is.
Gareth explains that ML can assist with:
Contact filtering & enrichment: Identify the person you want to get in front of, collect contact information (e.g. email address, social media handles), and mitigate human error (e.g. typos).
Processing data in inboxes: Read outreach emails, understand the urgency, sentiment, opinion and classify the semantics. Make a decision/action based on the text in emails.
Prospecting & list building: Scrape links, read page content, and analyse on-page attributes based on quality criteria to filter out unsuitable prospects. Classify the pages ready for manual inspection by a human team.
Media monitoring & email text extraction: Monitor PR tools, e.g. HARO, #journorequests, TalkWalker, keyword classify data, output grouped data for display (e.g. in a spreadsheet), and auto-respond.
Conversational: Employ psychology techniques in AI, auto-complete sentences, and suggest responses. (E.g. Gmail Smart Compose.)
And it will always feed back to the ML model when incorrect to make the process more accurate, efficient and intelligent.
- Identify the repetitive tasks: if it can be repeated, let ML do the heavy lifting to free you up for the human-only outreach tasks
- Anyone can implement ML (not just devs): There are plenty of platforms already built, from full ML platforms and send optimisation to data prediction and text analytics. You just need to hook it up to you tools via the API. Simple.
- Create more meaningful work: If you can let the bots identify the right sites, find contact details, select the appropriate subject line and triage your inboxes, you have more time to focus on building even more relationships and winning big links.