Are You Considering Behavior-Based Personalization?

If you are like most marketers, you’ve probably been salivating over personalizing your website for years. It has always seemed like a good idea, but it’s never seemed possible.

At first, you thought, “If Amazon can do it, we can do it!” But then your IT folks told you the way Amazon does it. Amazon has so many products and so many purchases in its history–and so many repeat visitors–that it is relatively simple to guess what people want. But your site isn’t like Amazon.

Then you thought, “Well, if we know something about our visitors, we can use that to personalize.” But no one wanted to register on your site, so you didn’t know who they were. And privacy regulations came along, and you weren’t sure you wanted to know anything.

Does that mean that you have to give up the dream? No!

You actually can personalize using your visitors’ behavior. With the right technology, you can watch what visitors do on your site. With a bit more technology, you can find the patterns that lead them to success. And with one last dollop of tech, you can use that data to suggest successful paths to others on that same journey.

That’s the beauty of behavior-based personalization. It doesn’t require registrations. It’s GDPR-compliant, because it doesn’t require any personally-identifiable information. It doesn’t require a a slew of products or  return visitors. Or heavy traffic.

If you’ve been waiting for the easy way to add personalization to your site, it’s time to check out behavior-based personalization.

Originally posted on Biznology

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About Mike Moran

Mike Moran is an expert in internet marketing, search technology, social media, text analytics, web personalization, and web metrics. Mike serves as a senior strategist for Converseon, a leading digital media marketing consultancy based in New York City. He is also a senior strategist for SoloSegment, a marketing automation software solutions and services firm.

Meet Intent-Based Content Recommendation

The new personalized approach to B2B content recommendation

Understanding customer intent is one of the most powerful marketing tools available to professionals. The right intent data will allow you to effectively connect potential customers to the content that is going to help them achieve their goal. So where do you find intent data? It exists in the systems you use today. Introducing “behavioral personalization,” a strategy to offer intent-based content recommendation. If you know where to look and you have the ability to mobilize that data you can use it to progress journeys, convert more business and win more often.

Intent: Let your customers tell you

We often talk about website search as being the most common personalized experience. Website visitors identify their need, and if the search engine works well it delivers the content that answers their question. It’s the simplest, most direct method of personalizing the customer experience. Personalization isn’t the only thing that search does. It is also the first inklings of the data you need to drive effective content recommendation.

The search box on any website fulfills not only the search term input function, but also gathers meaningful data about customer intent. This is the real source of search’s power. There are lots of topics that a searcher can query. Many of those also give you insight into why they’re asking those questions. Successfully deciphering intent can not only lead to better search results, but more importantly can lead to more conversions.

Simple Intent: The Keywords

Let’s consider two searches.

“Product X Value”

“Product Pricing”

It’s obvious that these searches will yield different results. If you deliver a results page with relevant content it will help the searcher move forward in their journey. But what’s more important than the topic they’re interested in is what the topic tells you about their intent.

That first term probably indicates someone who is in the interest phase of the process. They’ve gotten beyond the top of funnel messages and are going deeper. Not only are they going to need the right content to answer the question, they may be ready for messages that move them into consideration.

Nosing around pricing content is a clear indicator of someone who is considering a purchase. This is where journey progression becomes even more important. Answer the question effectively and they’re doing business with you.

Both these search terms give actional information about the intent of the visitor. They provide signals about what you should be serving them at this stage of the buying process.

Complex Intent: All that other data

Intentions that are apparent in search term data can also be found elsewhere. One of the most effective places to look for how intent manifests itself in your data is in your web analytics system.

The patterns in visitor journey data can illustrate intent very clearly. If someone is spending a lot of time with content that is in the consideration stage of your journey, that’s an obvious signal. But what if the signal is not readily apparent in the data?

This is where advanced data science tools can be brought to the challenge of understanding what the visitor is trying to achieve. For one of our clients, we’re beginning to use unsupervised machine learning techniques to interrogate tens of thousands of visitor journeys each month.

These methods help us construct models that show patterns of visitor behavior that are associated with intent. Once you can identify the snippets of behavior that are more closely associated with goals, you can understand what behavior signals intent for those goals. Knowing this you can recommend content at just the right moment to help drive visitors to those patterns.

The value of intent-based content recommendation

The value of intent-based content recommendation can be directly measured. Reduced exits and bounces that increase top of funnel progression are the first signals you’re onto something. You also likely have some conversions associated with specific tasks, such as downloads and contact forms, that can be directly measured.

Of course, what you really want to measure are the purchase conversions. In a B2B world making those connections can be difficult, especially if channel or field sales are a big part of your sales engine. However, you’ve been dealing with this challenge for long time. Instrument the tasks and activities that lead to contacts and monitor the activity. All things being equal, if you can reduce the top of funnel abandons (i.e. exits and bounces) you’re going to see more come out at the other end of the funnel.

Want to get started? We might be able to help. Connect with an expert right now.

Steve Zakur

About Steve Zakur

Stephen Zakur is CEO of SoloSegment. SoloSegment provides analytics that improve site search conversion and machine learning technologies that improve content effectiveness.

SearchChat Podcast: Is AI Bigger than the Internet?

In a recent study,  63% of CEOs agreed that AI will have more impact on their business than the internet. Think about that for a minute. The internet. And yet, 23% said they had no plans to do anything about it. Why? Partially, people tend to overestimate how much data they need to get to a reliable result for utilizing AI

Steve and I think it’s possible for most businesses to start implementing machine learning. The new exciting thing is behavioral personalization. Among privacy concerns and the world of GDPR, behavioral personalization is a way to use data that isn’t identifying. Instead, we can match patterns with other user’s patterns. You have more data than you think. You need less data than you think. And adequate new data is more accessible than you think.

What ways can you implement AI using the data you have now, to totally change the visitor journey? It’s about creating patterns and solving problems. Take a listen! And if you’re interested in learning what SoloSegment is about, feel free to connect with us.

0:00 Intro

1:50 Behavioral personalization changes customer experience

9:30 Are you planning for the AI future, now?

21:35 AI and behavioral personalization combine to create a new visitor journey

27:50 Outro

SearchChat is available on

Search Chat is SoloSegment’s podcast dedicated to all things search AI and content marketing related. Who is SoloSegment? We’re a technology company focused on site search analytics and AI driven content discovery to improve search results, increase customer satisfaction and unlock revenue for your company.

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About Tim Peter

Tim Peter is the President of SoloSegment. An expert in e-commerce and digital marketing strategy, web development, search marketing, and analytics, Tim focuses on the growth of the social, local, mobile web and its impact on both consumer behavior and business results. SoloSegment provides analytics that improve site search conversion and machine learning technologies that improve content effectiveness.

2019 Themes in Digital Marketing

This year has started off strong on my end, but we’re also looking ahead towards what’s next. I’ve spent a fair amount of time talking to digital marketing professionals about what’s important to them, sharing some of our product roadmap, and seeing where there’s alignment and where there may be market opportunity.

While I try to structure these conversations to touch on a few specific topics, things usually don’t go as planned. The diversity of industries, experience and job roles of the people means that each conversation takes a unique journey through the landscape.

During the discussions, three themes have emerged. I’m sure you’ll see some of your challenges and focus areas in these. We’ll be paying attention to these as we build solutions and go to market.

AI/Machine Learning gets tactical in 2019. Businesses will stop waiting for some magic bullet and start taking very specific shots at specific pain points, starting small, going fast and iterating to find value.

Getting started with ML can be difficult. But it’s necessary for marketers to keep your seat at the table. One executive I spoke to last week said that their way forward started with a domain where they had some expertise. They were in familiar territory. Familiar data, familiar business processes, and familiar business stakeholders made it easier to solve problems where they understand the value. The key learning point here is not to succumb to sales pitches for products that work on problems that you don’t fully understand. Find the familiar and start there.

For many of our customers  that means their starting with visitor journeys. They have lots of data that can be explored and mobilized in interesting ways that reduce exits and improve the overall customer experience.

Mid-Funnel content gets the attention it deserves. When I speak to content authors one of the laments that I hear frequently is the fact that landing pages and top of funnel content get most of the attention from digital marketing. At the other end of the journey, conversions are instrumented and waiting to be counted. But the paths between the two anchor points aren’t well understood and thus don’t always get focus on their importance in the conversion process. Content owners also are discouraged that they’ve produced something that basically gets ignored both internally and by customers and prospects.

From a product perspective, this is a place where we’re looking at the data we have around what happens after those initial success, whether it’s campaign driven or search driven, and figuring out how to use mid-funnel journey data to get the right content in front of prospects to extend journeys. Early signal from the data should allow us to start some beta work with customers in 2Q/3Q to figure out if this mid-funnel problem is fixable.

Data-driven automation improves productivity. A lot of on-website marketing activity continues to be hand crafted. The placement of content on pages, whether that content is static or rules-driven, continues to be a big part of the workload of B2B marketing teams. A marketing executive at a large tech company spoke of the challenge of dealing with website pages that aren’t part of their current marketing cadence. Getting the right calls to action, content recommendations, etc. doesn’t scale beyond the team.

Content recommendation engines can help here. Enabled by algorithms that look at a lot of the data your already have about visitors, journeys and content allow them to suggest content allowing marketing professionals to continue to focus on top priorities while putting data to work to help improve visitors who are elsewhere on the site.

I’m sure I’ll find other common topics as I speak with digital marketing professionals but this seems like a good list to focus on during 1Q. What are you top predictions for 2019? What are you focused on improving? Where are you learning? If you think we can help, connect with us.

Originally posted on Biznology

Steve Zakur

About Steve Zakur

Stephen Zakur is CEO of SoloSegment. SoloSegment provides analytics that improve site search conversion and machine learning technologies that improve content effectiveness.

Why AI Has Come a Long Way Since HAL in 2001

January is a special month in AI history. Because in both the novel and movie 2001: A Space Odyssey, January 12 is when the HAL 9000 sentient computer — (spoiler alert!) the story’s antagonistic artificial intelligence — goes live. Depending on whether you date HAL to its “birth” in the film, the novel, or when those media originated, HAL is anywhere between 22 years to 51 years old now (For trivia buffs, of which I’m one: The book and film were released in 1968, making HAL’s conception over 50 years ago; if you go by the dates given in the film or the book, respectively, HAL is either 27 or 22 years old). HAL is then placed aboard the Discovery One spacecraft to participate in a journey of, well, discovery to the planet Jupiter.

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About Tim Peter

Tim Peter is the President of SoloSegment. An expert in e-commerce and digital marketing strategy, web development, search marketing, and analytics, Tim focuses on the growth of the social, local, mobile web and its impact on both consumer behavior and business results. SoloSegment provides analytics that improve site search conversion and machine learning technologies that improve content effectiveness.

SearchChat Podcast: Can You Personalize Without Creepy Data?

Is the dream of the visitor journey dying? How do we make journeys more functional without using data people don’t want us to have?

Marketers are starting to learn they can’t just orchestrate a visitor journey from start to finish. It’s all about improving the journeys people actually make. They’re complex, not straightforward. Steve and I discuss how visitor journeys are a big data problem. Machine learning allows you not to have to manually deal with that data. It makes Big Data little.

Data can be put to work automatically to make the journey better — and it doesn’t have to be a ton of data. We often start with search data, and it works great since it connects people directly with the thing they want. “Behavioral personalization” means personalization but without all the creepy data. Instead, it’s personalization that customers are asking for. This matters in a post-GDPR world.

Google’s policy is to get right up to the creepy line without crossing it.  Most people don’t know that smart TVs are cheap because they are tracking your data.  How long will models built on creepy data survive?

The three laws of robotics initially were just about making sure robots don’t kill humans. Now we’re thinking much further beyond that — how to create ethical artificial intelligence for business. Interested in the podcast and behavioral personalization options? Check out SoloSegment’s technology solutions.

Tune in and discover more!

00m 00s — Intro and overview

2m 00s Visitor journeys are changing

7m 05s AI for developing visitor journeys

11m 05s Behavioral personalization

15m 25s Creepy Data

19m 30s 3 Laws of Robotics — how do we create ethical AI?

22m 45s Is it just “legal,” or is it good for customers?

29m 35s Outro

SearchChat is available on

Search Chat is SoloSegment’s podcast dedicated to all things search AI and content marketing related. Who is SoloSegment? We’re a technology company focused on site search analytics and AI driven content discovery to improve search results, increase customer satisfaction and unlock revenue for your company.

Originally published on Biznology

Avatar

About Tim Peter

Tim Peter is the President of SoloSegment. An expert in e-commerce and digital marketing strategy, web development, search marketing, and analytics, Tim focuses on the growth of the social, local, mobile web and its impact on both consumer behavior and business results. SoloSegment provides analytics that improve site search conversion and machine learning technologies that improve content effectiveness.

Do hidden robots need guiding standards too?

Even back in 1942, there were dreamers about what the days of artificial intelligence would look like. Futurists like Isaac Asimov were considering the risks of new autonomous technologies. It was during that year that Asimov wrote a short story entitled “Runaround” in which he unveiled the three laws of robotics.

The key theme for these laws was that a robot could not through action or inaction allow harm to come to humans. Over the years both philosophers and writers have examined these laws in myriad ways showing the loopholes in the language and the challenges that can arise in edge cases. Regardless, the principles seem like the sort of thing we’d want if robots walked among us. They should serve to enhance our lives.

If you’ve ever seen a video of Boston Dynamics’ robots, you understand why the three laws are needed, at least at an emotional level. Boston Dynamics makes all sorts of animal/human-like machines and they seem like something out of a science fiction movie where the robots are not benevolent servants but instead determined to be our overlords. The videos of those robots are evidence to support the need to get those laws right before Atlas walks among us.

But what about the hidden robots, the robots that exist only as lines of code buried on a web server in a cloud hosting facility and don’t look menacing? Should we also be giving thought to guiding principles of design for these engines that are fed our data and are allegedly supposed to make our user experience better?

It seems like a no-brainer. However, anyone can sign-up for their own cloud-based hosting account which likely includes a machine learning starter kit. With a little skill and the right data, a journeyman data scientist can create technology that can do things that would have seemed magical twenty years ago. In the hands of more talented operator far more extraordinary possibilities exist. So what responsibility do each of these developers have to society before they unleash their machines upon us?

I suspect that the European Union is going to lead in this space much as they did with privacy. I also suspect that the initial laws of robotics/AI are going to me more focused on disclosure than compliance with behavioral norms. But this is the sort of thing that could get out of hand, not in the Skynet manner but more in the way that Facebook struggled with privacy. I’ve written previously about whether business models based on personal data will survive. It seems the technology will be always two steps ahead of our understanding of how both it, and the humans who created it, will be using it.

I’m optimistic about the possibilities for AI to have an almost magical ability to improve many aspects our lives. But like with privacy, I think we have to be looking forward to the risks that such technology to have a negative impact. We need to be intentional about ensuring that the machines are learning to work to our benefit.

And if you want to learn more about personalization using behavioral data instead of personal information, check out our GuideBox technology.

Steve Zakur

About Steve Zakur

Stephen Zakur is CEO of SoloSegment. SoloSegment provides analytics that improve site search conversion and machine learning technologies that improve content effectiveness.

SearchChat Podcast: AI Goes Back to the Basics

We at SeachChat frequently talk about how AI and site search produce value for your site. But let’s break that down for a minute. What this is all about at the end of the day is customer experience.

When a prospective customer arrives on your site: are you helping them? Are you answering their question? What value might you be creating — for them, and for yourself?

Steve and I focus on some of the most important ways to fix your site search improvement program. It might not sound like the most glamorous solution, but it’s the best way to ensure you can capitalize on site search insights. Site search offers some valuable information: what can you learn about a visitor and their intent.

As I wrote recently, site search is your company’s best salesperson. When powered by AI, your site search learns about your prospective customers and can tailor results to guide them. Machine learning lets site search deliver results that drive sales. If a salesperson was performing as poorly as your site search, would you even keep them around?

And as always, to best improve your site search and utilize its data — drop us a line.

00m 00s — Intro and overview

02m 20s — Site search insights on Search Engine Land

13m 00s — Site search value and site search as your best salesperson

18m 50s — Developing a strong site search improvement program

23m 16s — AI and its connection to search

32m 30s — Customer experience

33m 23s — Subscription links and outro

SearchChat is now on

Search Chat is SoloSegment’s podcast dedicated to all things search AI and content marketing related. Who is SoloSegment? We’re a technology company focused on site search analytics and AI driven content discovery to improve search results, increase customer satisfaction and unlock revenue for your company.

Check us out on FacebookTwitter, or email info@solosegment.com.

Originally post on Biznology

Avatar

About Tim Peter

Tim Peter is the President of SoloSegment. An expert in e-commerce and digital marketing strategy, web development, search marketing, and analytics, Tim focuses on the growth of the social, local, mobile web and its impact on both consumer behavior and business results.

SoloSegment provides analytics that improve site search conversion and machine learning technologies that improve content effectiveness.

How long will business models based on personal data survive?

I don’t use Snapchat mostly because nobody I know uses it. I’m not the target demographic, apparently. But that doesn’t keep me from talking about how much I dislike the user experience. I know that when I register such complaints I probably sound like a codger who wants his buggy whip back. But even so, I never really “got” why someone would build a platform where content is ephemeral. Isn’t the whole point of social platforms to catalog our lives? Maybe I’m missing something.

Steve Zakur

About Steve Zakur

Stephen Zakur is CEO of SoloSegment. SoloSegment provides analytics that improve site search conversion and machine learning technologies that improve content effectiveness.