Louisa is SEO editor at the LA Times and I feel a little overwhelmed by her and the institution that is the LA Times. First thing to know is that Louisa is there to educate the journalists rather than messing with their style. She is the stabiliser wheels for people who have 40 years of career behind them, which is cool. Moving an institution like this to a digital approach is a big, big deal. Then onto the European directive that aims to protect publishers. Louisa looks at it from the publishers point of view, I try to defend Google. Louisa then suggests a compromise and we move on very naturally to find a solution for a world where everyone is happy.
I quickly state that I won’t ask about ranking factors, just the way Bing ranking works (to try to get some confirmation of Darwinism in search). Frederic is the 10 blue links guy. The team in the next office do the Q and A…. and then there is a Whole Page Team, which is an interesting development for me (since my Darwinism theory takes a SMALL hit :( All the rich elements function of the same algorithm with different weightings… but with a master ‘whole page algorithm’ that brings it all together. And Ads work on the same principle as other rich elements, which is terribly important (to me). Always remember that algorithms are built on human intuition, even when we use machine learning. In terms of machine learning in ranking algorithms, we need to talk about features, not factors. Then onto how pancakes and omelettes (I get confused) can help us better (batter ??) understand machine learning (and thus ranking). Each team of judges (raters) are looking at the value a specific element brings (blue links, video, answer etc.) We also get the serious UnGagged interview at the end.
Slightly uncomfortable moment at the start. I then try to be professional. Not sure if I carry it off. Jerry tells me how great UnGagged is. Then we move onto doing something – the small things effectively. And then the 5 things people can start to do to move your business forwards. A lot of it is simple common sense. And we miss that more often than not. Jerry gives me a good lip twitch that is now a ‘thing’ :) Jerry answers the question as to how much it can cost to flip a switch. Then onto swapping goat stories.
Eric loves UnGagged. Then we discuss what is things to focus on in what stage of your startup journey, including which keywords. We get onto the importance of branding, brand SERPs and bringing the offline online. And when a query can be a mix of informational, transactional, and navigational. There is a lovely break where we discuss stuff ‘off-record’, that I left in because we completely forgot to discuss what we decided to discuss during the break.
Along with Greg Gifford, Arsen Rabinovich, Jennifer Hoffman starts with why technical SEO pays. A bit of a discussion about bells, whistles, heavy images and mega comment threads leading to poor onsite experience in terms of load time. Then onto navigation and indexation. And tracking user behaviour, the Knowledge Graph, entity optimisation… and brands as entities. We end with the importance of spring cleaning.
Sitting in two comfy armchairs, looking at the sea in Brighton. We start with a chat about machine learning in Google’s search algorithm, PageRank and then onto the Knowledge Graph. There are less entities in the world than webpages. So Google’s job is easier. But the Knowledge Graph is biased – the seed set for google’s understanding is a bunch of librarians (aka Wikipedia editors) who have little in depth knowledge on the topics they edit, especially in anything that is not within their culture. We happily grab examples from the surrounding environment. Piers become a central point, and piers in Ethiopia in particular. We move onto fan sites, that are not necessarily accurate, and perhaps people believe that William Shatner is a space man. Errors such as that at the start of a seed set will mean learning is biased and perhaps inaccurate… and can quickly spiral out of control. They are building on what Dixon calls ‘areas of light’, but that is biased too. One problem is that genuinely good new ideas are going to have trouble surfacing because of the bias against ideas that are not popularly held belief. We move onto loops of truth and self-fulfilling prophecies. Fake news gets a look in (of course). As does bad fact checking. Then we finish off with InLinks – Dixon’s super new SaaS for automatically building internal knowledge graphs and writing scheme.org structured data on the fly. I ask a trick question, and Dixon deals with it rather well. And we end by coining the phrase ‘The Wikipedia model’.
Susan insists that voice search is happening faster than we think. 5 years, not 10. Half life theory comes into play with technology. Don’t underestimate “Call mom”. Then we have the great debate about the amount of voice data. And Susan nails her argument by identifying what are the fallbacks for these machines? Interestingly, even if we think the answers / system is weak now, that doesn’t mean we aren’t going somewhere very interesting very fast. Susan acronyms. I keep using them. But they are ambiguous. So she convinces me again… I agree. featured snippets are super important (and super exciting).
We start talking about building community. David gives some great tips – he has 22,000 people in his genius community who share 50,000 messages a month, so he knows what he’s talking about. he points out we all have a community whether we know it or not. We talk about implicit and explicit communities, then have a debate about the word ‘crumbs’. But then David turns the table on me brilliantly by asking about the red t-shirt… and the second half is him getting me talk about the digital nomad lifestyle and the podcast. My initial though was to only publish the first half. But David does a great job as interviewer, so I left it all. Warts and all ! At the end Susan Westwater (the previous podcast guest) joins in because she thinks we are just having a chat (and not recording a podcast). Finally, right at the end, we end with a Mexican standoff.
We start with a delightful chat about New York, Halloween and even get a quick (made up) Broadway ditty. Then onto E-A-T and how this is affecting our approach to digital marketing. You need to get your information more accurate with help from experts. The problem comes from the fact that the returns aren’t immediate, which is a problem for a lot of people since their job often depends on fast results and quick returns. Is there a quick-win cheat? And is Google a chicken with its head cut off (terribly good analogy for Halloween)?
We start with an idiotic James Bond analogy. Paul pulls me back to the serious business of ‘what is technical SEO’? And the definition is wider than I thought. 4 types of tech SEO. Paul has a plan to tell me the 4 types. Like a child, I keep trying to jump ahead. Paul then looks at skillsets and venn diagrams. And that we should look at (and accept and appreciate) these crossovers. SEO is one giant Venn diagram of skillsets. Then onto the fact that in SEO we are (and need to be) multi-skilled. We end with ‘it’s important to get into the weeds’. Who knows what that means (ask Paul)