While the way that businesses have used marketing campaigns over the years has changed, the reasons have not. Every business wants to reach its ideal customer just when that customer needs it.
With the constant flux of new technologies, the way that companies need to reach these customers has to evolve to make up the difference.
Here are 6 digital marketing trends to consider for your 2019 marketing strategy.Digital Marketing Trend #1: Omnichannel Marketing
Today’s consumer uses multiple channels to research, compare, buy from and interact with businesses. These can be both online and offline channels, and the latter include your own website as well as Amazon, eBay, Facebook, etc.What is omnichannel marketing?
Omnichannel marketing is a type of marketing that connects the dots between multiple channels, ensuring a consistent user experience and encouraging the consumer to engage with your brand at every touchpoint across multiple channels.
Th... Read More
In November 2018, Google released an updated PageSpeed Insights API, which provides performance reports from both lab and field data on a page. Using the PageSpeed Insights API, we can test multiple URLs at once to get a better idea of our site’s overall performance and identify areas of our site that can be optimized for speed. To do this, I wrote a script that uses the new PageSpeed Insights API to retrieve performance data and print the results in a Google Sheet—the easiest and quickest way to get an overview of your site’s speed using a sample of pages.
Before you follow optimization recommendations from PageSpeed Insights, it’s important to note that the tool often recommends actions that won’t improve user experience or provide a worthwhile performance increase for your specific site. For example, PageSpeed Insights may advise caching external files (e.g. requests to Facebook.com) or serving images in &... Read More
Don’t get us wrong: we love good-looking landing pages. The way the colors contrast to draw attention; the striking custom photography and animation; the elegant application of negative space and rule-of-three layouts. Seriously, these things keep us up at night.
But here at Unbounce, we know that there’s more to a landing page than looks. We want the kind of page that won’t embarrass you when you bring it home to your CMO. One that you can really, you know… build a campaign with.
What we really want is a landing page that converts.What Makes a High-Converting Landing Page?
(“Yeah, yeah, take me to the high-converting landing page examples!”)
People have created a lot of landing pages with the Unbounce Builder (like, so many, you guys), so we think we’ve got a pretty good understanding of what makes a page convert. Over the years, it’s become clear that nearly all successful landing pages have some key elements in comm... Read More
Identifying Primary Versions of Duplicate Pages
We know that Google doesn’t penalize duplicate pages on the Web, but it may try to identify which version it prefers to other versions of the same page.
I came across this statement on the Web about duplicate pages earlier this week, and wondered about it, and decided to investigate more:
If there are multiple instances of the same document on the web, the highest authority URL becomes the canonical version. The rest are considered duplicates.
~ Link inversion, the least known major ranking factor.unsplash-logoLuke Leung
I read that article from Dejan SEO about duplicate pages, and thought it was worth exploring more. As I was looking around at Google patents that included the word “Authority” in them, I found this patent which doesn’t quite say the same thing that Dejan does, but is interesting in that it finds ways to distinguish between duplicate pages on different domain... Read More
How A Knowledge Graph Updates Itself
To those of us who are used to doing Search Engine Optimization (SEO), we’ve been looking at URLs filled with content, and links between that content, and how algorithms such as PageRank (based upon links pointed between pages) and information retrieval scores based upon the relevance of that content have been determining how well pages rank in search results in response to queries entered into search boxes by searchers. Web pages connected by links have been seen as information points connected by nodes. This was the first generation of SEO.
Chances are good that many of the methods that we have been using to do SEO will remain the same as new features appear in search, such as knowledge panels, rich results, featured snippets, structured snippets, search by photography, and expanded schema covering many more industries and features then it does at present.
Search has been going thr... Read More
Your latest content campaign has been covered by a top-tier global publication… but there’s no link! Your brand (or your client) has been mentioned, but that’s all.
At this stage, do you simply accept the brand value of a mention and move on to target your next link prospect? Or is there a process you can follow to at least try to get a link added in?
Sadly, unlinked brand mentions are one of the biggest challenges when building links through content marketing and digital PR. It’s more common than many link builders would like to admit.
But, seeing a link added in to an article after it’s been published can be easier to achieve than many assume.
You just need to know when it’s right to ask for a link, who you need to reach out to and what you should say. We’ll cover all these things below.
Content-led link building is hard — don’t let anyone tell you otherwise.
It often takes blood, sweat and tears to launch... Read More
PebblePost, the inventor of this Programmatic Direct Mail® alternative, helps brands connect with consumers in a way that avoids the blowback made by consumable electronic advertisements. We use programmatic technology to analyze what consumers are doing in real time on their websites -- then send a tangible, relevant, and personalized Programmatic Postcard or Programmatic Catalog for their homes. We provide consumers that they can hold within their palms, and trigger on at the time they choose.
PebblePost and Establish by Adobe form a wonderful tag team.
The synergies between the Programmatic Direct Mail® solution and Ad... Read More
It’s a new year, and you know what that means: new annual predictions. ‘Tis the season for companies to publish their thoughts and plans for 2019, including us. And we’re betting on big changes, like the growing importance of the customer experience and artificial intelligence (AI).
Our forecasting is based on research and deep knowledge of industry trends. But technology is always evolving—sometimes by leaps, but often by tweaks—so it can be difficult to notice incremental changes. That’s why we find it helpful to glance back over our shoulders to see just how far we’ve come.
Take the iPhone, for example. A decade ago, the smartphone was a year and a half old and only beginning to infiltrate schools, offices, and dinner tables. Now, the technology is ubiquitous. It’s hard to imagine life before—or without—smartphones. In 10 short years, Apple has had a tremendous impact on society.
We believe that AI has the potential to create a paradigm sh... Read More
Sura gave up on her debugging for the moment. “The word for all this is ‘mature programming environment.’ Basically, when hardware performance has been pushed to its final limit, and programmers have had several centuries to code, you reach a point where there is far more signicant code than can be rationalized. The best you can do is understand the overall layering, and know how to search for the oddball tool that may come in handy—take the situation I have here.” She waved at the dependency chart she had been working on. “We are low on working fluid for the coffins. Like a million other things, there was none for sale on dear old Canberra. Well, the obvious thing is to move the coffins near the aft hull, and cool by direct radiation. We don’t have the proper equipment to support this—so lately, I’ve been doing my share of archeology. It seems that five hundred years ago, a similar thing happened after an in-system war at Torm... Read More
I refuse to watch Game of Thrones.
Why? Because a surefire, tried-and-true way to guarantee that I won’t watch something is to tell me that I have to watch it.
Oh, do I have to watch Game of Thrones? Do I really? Is it really that important that I consume one of the most critically acclaimed, universally adored, and culturally relevant pieces of entertainment of this decade?
My refusal to watch the things people tell me to watch is probably tied to some deep, unrelenting psychological drive to maintain complete control over my own life. But that’s neither here nor there.
I’m breaking my own rule today. Although it’s something I’ve championed against for several years now, I’m going to recommend some podcasts I think you’ll all appreciate.
Do you have to listen to any of these? Nah. Would it behoove you to check some of them out? You better believe it, pal. Each one brings unique ex... Read More
"How do you do it?"
This the question I get asked the most when it comes to my extensive (and often frenetic) business travel pace. Once I break it down, most people realize that life (and business travel) can be a lot less complicated and stressful if you plan, and seek out the advice from others who have paved the way (and paid the price). After one million miles of business travel, and being a huge nerd/fan of everything associated with it (from best travel apps and gear to the perfect luggage and airport comfort), I'm passionate about business travel (and making it a better experience).
So, how do I do it? How should you do it?
I sat down with my old friend, Bryan Eisenberg, who recently started a show called, Business Travel Hacks, to discuss everything... in gory detail... that I have learned about business travel, and how to make it better. Whether you're on the road for client meetings, to pitch new business, attend trade shows or speak at conferences, t... Read More
Context Clusters and Query Suggestions at Google
A new patent application from Google tells us about how the search engine may use context to find query suggestions before a searcher has completed typing in a full query. After seeing this patent, I’ve been thinking about previous patents I’ve seen from Google that have similarities.
It’s not the first time I’ve written about a Google Patent involving query suggestions. I’ve written about a couple of other patents that were very informative, in the past:
- 6/10/2016 – Google Entity Search Suggestions Patent (Associating an entity with a search query)
- 5/26/2010How a Search Engine Might Identify Possible Query Suggestions (Generating query suggestions using contextual information)
In both of those, the inclusion of entities in a query impacted the suggestions that were returned. This patent takes a slightly different approach, by also looking at context.
Context Clusters in Query Suggestions
We’ve been seeing the word Context spring up in Google patents recently. Context terms from knowledge bases appearing on pages that focus on the same query term with different meanings, and we have also seen pages that are about specific people using a disambiguation approach. While these were recent, I did blog about a paper in 2007, which talks about query context with an author from Yahoo. The paper was Using Query Contexts in Information Retrieval. The abstract from the paper provides a good glimpse into what it covers:
User query is an element that specifies an information need, but it is not the only one. Studies in literature have found many contextual factors that strongly influence the interpretation of a query. Recent studies have tried to consider the user’s interests by creating a user profile. However, a single profile for a user may not be sufficient for a variety of queries of the user. In this study, we propose to use query-specific contexts instead of user-centric ones, including context around query and context within query. The former specifies the environment of a query such as the domain of interest, while the latter refers to context words within the query, which is particularly useful for the selection of relevant term relations. In this paper, both types of context are integrated in an IR model based on language modeling. Our experiments on several TREC collections show that each of the context factors brings significant improvements in retrieval effectiveness.
The Google patent doesn’t take a user-based approach ether, but does look at some user contexts and interests. It sounds like searchers might be offered a chance to select a context cluster before showing query suggestions:
In some implementations, a set of queries (e.g., movie times, movie trailers) related to a particular topic (e.g., movies) may be grouped into context clusters. Given a context of a user device for a user, one or more context clusters may be presented to the user when the user is initiating a search operation, but prior to the user inputting one or more characters of the search query. For example, based on a user’s context (e.g., location, date and time, indicated user preferences and interests), when a user event occurs indicating the user is initiating a process of providing a search query (e.g., opening a web page associated with a search engine), one or more context clusters (e.g., “movies”) may be presented to the user for selection input prior to the user entering any query input. The user may select one of the context clusters that are presented and then a list of queries grouped into the context cluster may be presented as options for a query input selection.
I often look up the inventors of patents to get a sense of what else they may have written, and worked upon. I looked up Jakob D. Uszkoreit in LinkedIn, and his profile doesn’t surprise me. He tells us there of his experience at Google:
Previously I started and led a research team in Google Machine Intelligence, working on large-scale deep learning for natural language understanding, with applications in the Google Assistant and other products.
This passage reminded me of the search results being shown to me by the Google Assistant, which are based upon interests that I have shared with Google over time, and that Google allows me to update from time to time. If the inventor of this patent worked on Google Assistant, that doesn’t surprise me. I haven’t been offered context clusters yet (and wouldn’t know what those might look like if Google did offer them. I suspect if Google does start offering them, I will realize that I have found them at the time they are offered to me.)
Like many patents do, this one tells us what is “innovative” about it. It looks at:
…query data indicating query inputs received from user devices of a plurality of users, the query data also indicating an input context that describes, for each query input, an input context of the query input that is different from content described by the query input; grouping, by the data processing apparatus, the query inputs into context clusters based, in part, on the input context for each of the query inputs and the content described by each query input; determining, by the data processing apparatus, for each of the context clusters, a context cluster probability based on respective probabilities of entry of the query inputs that belong to the context cluster, the context cluster probability being indicative of a probability that at least one query input that belongs to the context cluster and provided for an input context of the context cluster will be selected by the user; and storing, in a data storage system accessible by the data processing apparatus, data describing the context clusters and the context cluster probabilities.
It also tells us that it will calculate probabilities that certain context clusters might be requested by a searcher. So how does Google know what to suggest as context clusters?
Each context cluster includes a group of one or more queries, the grouping being based on the input context (e.g., location, date and time, indicated user preferences and interests) for each of the query inputs, when the query input was provided, and the content described by each query input. One or more context clusters may be presented to the user for input selection based on a context cluster probability, which is based on the context of the user device and respective probabilities of entry of the query inputs that belong to the context cluster. The context cluster probability is indicative of a probability that at least one query input that belongs to the context cluster will be selected by the user. Upon selection of one of the context clusters that is presented to the user, a list of queries grouped into the context cluster may be presented as options for a query input selection. This advantageously results in individual query suggestions for query inputs that belong to the context cluster but that alone would not otherwise be provided due to their respectively low individual selection probabilities. Accordingly, users’ informational needs are more likely to be satisfied.
The Patent in this patent application is:
(US20190050450) Query Composition System
Publication Number: 20190050450
Publication Date: February 14, 2019
Applicants: Google LLC
Inventors: Jakob D. Uszkoreit
Methods, systems, and apparatus for generating data describing context clusters and context cluster probabilities, wherein each context cluster includes query inputs based on the input context for each of the query inputs and the content described by each query input, and each context cluster probability indicates a probability that at a query input that belongs to the context cluster will be selected by the user, receiving, from a user device, an indication of a user event that includes data indicating a context of the user device, selecting as a selected context cluster, based on the context cluster probabilities for each of the context clusters and the context of the user device, a context cluster for selection input by the user device, and providing, to the user device, data that causes the user device to display a context cluster selection input that indicates the selected context cluster for user selection.
What are Context Clusters as Query Suggestions?
The patent tells us that context clusters might be triggered when someone is starting a query on a web browser. I tried it out, starting a search for “movies” and got a number of suggestions that were combinations of queries, or what seem to be context clusters:
The patent says that context clusters would appear before someone began typing, based upon topics and user information such as location. So, if I were at a shopping mall that had a movie theatre, I might see Search suggestions for movies like the ones shown here:
One of those clusters involved “Movies about Business”, which I selected, and it showed me a carousel, and buttons with subcategories to also choose from. This seems to be a context cluster:
This seems to be a pretty new idea, and may be something that Google would announce as an availble option when it becomes available, if it does become available, much like they did with the Google Assistant. I usually check through the news from my Google Assistant at least once a day. If it starts offering search suggestions based upon things like my location, it could potentially be very interesting.
User Query Histories
The patent tells us that context clusters selected to be shown to a searcher might be based upon previous queries from a searcher, and provides the following example:
Further, a user query history may be provided by the user device (or stored in the log data) that includes queries and contexts previously provided by the user, and this information may also factor into the probability that a user may provide a particular query or a query within a particular context cluster. For example, if the user that initiates the user event provides a query for “movie show times” many Friday afternoons between 4 PM-6 PM, then when the user initiates the user event on a Friday afternoon in the future between these times, the probability associated with the user inputting “movie show times” may be boosted for that user. Consequentially, based on this example, the corresponding context cluster probability of the context cluster to which the query belongs may likewise be boosted with respect to that user.
It’s not easy to tell whether the examples I provided about movies above are related to this patent or if it is tied more closely to the search results that appear in Google Assistant results. It’s worth reading through and thinking about potential experimental searches to see if they might influence the results that you may see. It is interesting that Google may attempt to anticipate what is suggests to show to us as query suggestions, after showing us search results based upon what it believes are our interests based upon searches that we have performed or interests that we have identified for Google Assistant.
The contex cluster may be related to the location and time that someone accesses the search engine. The patent provides an example of what might be seen by the searcher like this:
In the current example, the user may be in the location of MegaPlex, which includes a department store, restaurants, and a movie theater. Additionally, the user context may indicate that the user event was initiated on a Friday evening at 6 PM. Upon the user initiating the user event, the search system and/or context cluster system may access the content cluster data 214 to determine whether one or more context clusters is to be provided to the user device as an input selection based at least in part on the context of the user. Based on the context of the user, the context cluster system and/or search system may determine, for each query in each context cluster, a probability that the user will provide that query and aggregate the probability for the context cluster to obtain a context cluster probability.
In the current example, there may be four queries grouped into the “Movies” cluster, four queries grouped into the “Restaurants” cluster, and three queries grouped into the “Dept. Store” cluster. Based on the analysis of the content cluster data, the context cluster system may determine that the aggregate probability of the queries in each of the “Movies” cluster, “Restaurant” cluster, and “Dept. Store” cluster have a high enough likelihood (e.g., meet a threshold probability) to be input by the user, based on the user context, that the context clusters are to be presented to the user for selection input in the search engine web site.
I could see running such a search at a shopping mall, to learn more about the location I was at, and what I could find there, from dining places to movies being shown. That sounds like it could be the start of an interesting adventure.
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Writing a good article is not enough for search visibility and good user engagement. What really matters is how well you structure it in order to optimize it well and give clear answers to users’ questions.
Here are four factors to consider when creating effectively structured content, and tools to use for each.
1. How to use your HTML headings
HTML headings are nothing new. In fact I was blogging on them over a decade ago (back then we referred to them as “semantic structure” which gives a good idea what they are for).
HTML headings got back into the spotlight recently thanks to Google’s featured snippet algorithm.
We have found that Google looks for an H2/H3 subheads to locate the best answer to the query (and consequently feature the page).
Since featured snippets are also powering voice search results for the most part, we’ve seen a flood of newer articles on structuring your content with HTML headings over the past few months.
Here are a few takeaways on how to use HTML headings correctly:
- Keep the content structure in mind. You don’t start your page with an H3 heading. Instead, it should H1 heading followed by an H2 heading followed by a few H3 headings. There can be several H2 and H3 headings within one article reflecting the hierarchy of content.
- HTML headings are your perfect sections to put your primary and secondary keywords in. It’s not just for SEO (although it is important): Your readers will skim through your content and seeing those keywords (that brought them there) in prominent places will keep them reading.
- When taken out of context, H2-H3 headings should give a good idea of what the article is about. It’s like a summary of a page.
- Each heading should be followed by a clear concise answer (e.g. a definition, a quick factual answer, etc.) This is for both search engines and readers to quickly find what they were looking for.
There are not many tools currently providing actionable optimization recommendations when it comes to content structuring. I usually turn to question research when I want to better understand how to break my article into subtopics.
To better understand how to word my headings, I am using Text Analysis by Serpstat. The tool is based on Keyword Clustering feature (which I highlighted here), so your first step would be grouping your keyword list using that section. Once you identify semantic groups of your keywords, select one (or several) of the groups and proceed to the Text Analysis step.
The tool will analyze on-page content of your top 10 organic competitors in Google and come up with the optimization recommendations to create a better-optimized copy (and structure):
Read a more in-depth explanation of the feature here.
2. How to better optimize each article section
SEO has moved beyond keyword matching. While knowing your primary keyword(s) is still very important, using it throughout your article is not enough to optimize it.
How to better structure each section of your article?
TextOptimizer, the tool I have already highlighted here, makes the topic research even easier with its latest update. The tool uses semantic analysis to come up with the list of related and neighboring terms that should be covered in your article or on your landing page.
On top of all, you can clearly see what you should discuss within each section of your content. To give you a better idea, let’s say you are working on a landing page for your [social media marketing] services.
TextOptimizer will search Google for that query, extract search snippets and, using semantic analysis, identify key concepts that will best cater to Google’s and its users’ expectations. One of those identified terms is, say, “Business goals” which you may decide to cover under a separate HTML heading.
But what should be inside that section?
Clicking the phrase inside TextOptimizer’s dashboard will give you a very clear idea:
What you need to do now is to create a copy discussing several of these concepts inside your section covering “Business goals“.
3. Where and how to use your calls-to-action
In-content calls-to-action are often neglected. This is unfortunate because content is a massive lead driver, especially once you get it well-placed in Google’s search results (using the two tools above).
But how to turn your content into a conversion and / or lead generation channel?
Make the most of your in-content CTAs (including in-content two-step optin).
Finteza is the free analytics software with a solid focus on conversion rate optimization. It tracks your multiple CTAs and tells you exactly how your readers engage with them.
Finteza makes it super easy to add in-article CTAs to event tracking through their WordPress plugin:
Tip: When adding your in-content events for tracking, name them based on the placement to better understand which of those perform better. For example, “article-top download”, “sidebar banner”, “post-text webinar”, etc.
4. How to use in-content structured markup
Finally, if you really want to make the most of your content structuring, schema.org is always a good idea. When it comes to content, there are only a few schema.org types currently officially supported by Google including reviews, recipes and news.
One of the non-supported types which I am inclined to use is HowTo schema which we already saw used by Google as an experiment.
[Screenshot by Aaron Bradley]
Yoast Plugin makes it super easy to implement.
Tip: Use Yoast SEO plugin to easily add HowTo schema: Just keep adding steps until you’ve included all of them. This will help Google to better locate and interpret your instructions.
Content creation is the fundamental step in any digital marketing strategy, even in difficult niches. Make the most of your content development efforts with better structuring each page that goes up on your site.
What tools are you using to structure your content? Please share your tips!
The post Four tools to better structure your article for SEO and usability appeared first on Search Engine Watch.
Bing’s keynote in the event how intelligent image search will expand and took a closer look in hunt integration for internal records.
Please see Internet Search Engine Land to the article.
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