Must Marketers be Data Scientists?

Big data is having big effects on content marketing, nowhere more than in its ability to make sense of the complexity of human language. Understanding data science is necessary for agile marketing in 2019. Here’s how marketers can utilize data to hone their craft.

Mining for Meaning

Most web content consists of unstructured text. Mining this text for meaning and relevance is what search engines do. Search engines provide you with what they think are the most relevant and meaningful experiences, based on your search keywords. Understanding those results is the primary clue agile marketers use to better understand audience intent.

How does this work? Search engines are giant natural language processing engines that produce an urban dictionary full of definitions of keywords based on how they are used in digital media. In a sense, search engines “understand” how we use natural language over time. (This is why there’s so much hidden value in site search.)

Testing out Answers

The clues from this natural language processing rarely lead to cut-and-dried answers but are analyzed as statistics. Agile marketers use the data to make decisions about information their target audiences are the most likely to need. They provide the information in ways they think will be most useful to them. But, all things considered, multiple versions of the same information are equally likely to serve audience needs. This is where agile marketers are equally likely to serve audience needs. Marketers become data scientists–by serving multiple versions of the same digital experiences randomly to their audiences and testing the results. The experiences that get the best results win. 

This technique, known as A/B testing or multivariate testing, yields performance data that provides an ever-more-clear picture of how to better serve the target audience. A/B testing pits one variant against another (A vs. B) while the more powerful multivariate testing allows hundreds of even thousands of possibilities to compete with each other for supremacy. Patterns that tend to yield better results can be used as shortcuts by other digital marketing teams within the organization.

Agile Marketing is Machine Learning

In this way, agile marketing can sometimes be thought of as a form of machine learning, where the inputs of the machine are the practices and the outputs are improved performance. As the machine gets ever better at detecting working patterns for the target audience, it “learns” to optimize digital assets over time.

The machine is not just an optimization engine, however. The machine is a prioritization engine. Every marketer is faced daily with a challenge to do more with less. That means continually examining the mix of activities and weeding out poor performers and building new ones in their place, based on the data.

The market is constantly in flux, and a savvy marketer is continuously adjusting the ix to match shifting audience needs and business priorities. That’s why behavioral data is the next step in the game: incorporating your visitor’s behaviors to truly understand your intent and adapt to it. This kind of agility was not possible prior to digital marketing. Now it is table stakes.

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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.

The 1H B2B Marketing Restrospective

The second quarter is behind us which also signals the end of the half. So what’s next?

Here in the US we’re taking vacations to recharge. No matter how much disconnecting we do, in those quiet moments we’re reflecting. We’re wondering about where we left money on the table and how we’re going to adapt our plays so that we win more in the coming months.

The Marketing Restrospective

In agile software development the team spends time at the end of each sprint performing a self review. This review is called a retrospective. The retrospective is a relatively brief meeting that seeks to answer three questions:

  1. What worked well for us?
  2. What did not work well for us?
  3. What actions can we take to improve our process going forward?

The purpose is not reflection on outcomes.  The purpose is to reflect on the methods the team used to produce the outcomes. The goal is to become better at creating great work. By honing the abilities of the team, the outcomes will improve in a sustainable manner. 

There’s a popular point of view that every function can be “agile.” I don’t think that’s true. Agile lends itself to work that can deliver value in an episodic manner. Not all work can be done in this manner. But that doesn’t mean we can’t learn something from agile about continuous improvement of the process.

At the heart of the retrospective is an assessment, by the team, of how well the marketing business processes worked, the identification of places where the process can be improved, and a finite set of actions that are going to be taken to improve the process. Let’s see how that works.

The Three Retrospective Questions

What worked well for us?

This seems like the simplest question but it can be a challenge to answer. There is not always consensus across the team. The purpose of this question is not only to celebrate success but also to eliminate things for the next question. Often things that are going well can be honed but resist the urge to oversharpen.

What did not work well for us?

This is the question that is both critical to improvement and a potential trap. Misery loves company and it’s easy to fall into a death spiral of complaints and commiseration. The key is to focus and prioritize. Agile teams know how to do this because they plan their work this way.

For teams less experienced in agile planning, it’s important to timebox this activity. Get the list out. Don’t spend too much time assessing it at first. Once the first pass is on the board, have the team vote on which are the most important things that didn’t work well so that you have a prioritized list of the most important gaps in performance. 

If it’s helpful you can use a grouping methodology like: “People, Process, and Platform” to organize the opportunities.

What actions can we take to improve our process going forward?

This is where the rubber meets the road. Which of those things are you going to select to work on and actually deliver improvement in the near-term? This is another time box. While you may not work day-to-day in sprints, this is where you’re going to have to commit to delivering improvement in 30 days. 

Why 30 days? There’s nothing magical about that timeframe but it is set in stone. You have 30 days to make a difference.

Go back to your list. Are the problems/opportunities granular enough that you can do something in 30 days? If not, refactor the list until you have 30 day “doable” actions in a prioritized list.

Finally select what you’re going to work on and deliver in 30 days. Remember, you have to do this stuff in addition to your team’s day job. At the beginning set your sights low. Get a sense of your capacity by delivering improvements. When you’re more experienced you can take bigger more aggressive bites.

Developing good habits

One of the most interesting things about agile development is the focus on continuous improvement of the process. It’s built into how the work gets done. In other business functions improvement is often a project, not a process. Your team’s challenge is to make improvement — reflection, planning, execution — a coequal part of their work regiment. 

Conduct your 1H retrospective. Don’t spend more than four hours on the work. Choose your actions and get started. But don’t wait until the next half to repeat the process. Do it every 30 days. Rinse and repeat. Build improvement into your process. Achieve your objectives. Grow your business.

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.

What’s Inside Behavioral Data?

Personas have been used for a number of years by B2B digital marketers to craft content that aligns with a visitor’s context. But we all know that personas are also so… 2015. The rise in personalization has revealed both the limits and challenges of persona-based content creation — creating and maintaining content for every persona is a lot of work and getting that content in front of the visitor at the right time is tricky.

Move from personas to personalization

In order to get that content in front of the right person, you have to know a bit about the visitor. Usually that’s done with either first party or third party data that you’ve gathered or obtained about the visitor. But both regulatory changes (see GDPR) and industry practices (see ITP 2.1) are going to limit the effectiveness of such tracking in the near future. So you’re going to have to take a different approach to identifying and segmenting users.

Using behavior data and contextual data for segmentation is one way to be able to deliver relevant content in an environment where persona data may not be available. With this approach, visitors don’t need to hand over any personal data for you to best understand who is visiting your site and what their goals are, and what content they need to see to progress their journey.

There are two types of behavioral data 

  1. Historical behavior: What pages have they visited? What have they viewed on the site? What articles did they read? Where have they clicked? What content have they downloaded? Marketers (especially with the help of advanced technology like text analytics and machine learning) can make use of all of this aggregate behavioral and contextual data to model patterns that are associated with task achievement. 
  2. Real-time behavior: Models are great, but putting them to work is where the magic happens. The real-time data related to a  particular customer’s experience (the pages they look at and the context of those pages)is compared to the model. Task predictions take place and content effective at progression towards those tasks are presented to users. At a minimum, contextual data can be used to recommend related content.

Understanding past behavior is the critical input to being able to predict effective future journeys. This type of personalization reduces the workload on content creators because it maximizes the use of content that you already have on your website. It’s also content that your visitors have already told you is effective. 

How do you use behavioral personalization on your site?

Getting started with personalization can be difficult. Many integrated MarTech stacks include personalization capabilities but many companies don’t use those capabilities. Often that comes down to one of two choke points: IT teams enabling some of the capability, and/or content teams creating the content to be presented.

Behavioral personalization can mitigate some of those concerns by using the content that you already have, data that’s readily available, and easy to deploy technologies to offer content suggestions that progress journeys towards completion. 

Despite fitting your persona classification, your visitors and prospects are wildly diverse with no two achieving their objectives in the same way. No amount of information about demographics or firmographics will help solve that journey diversity problem. Behavioral data packs a wealth of knowledge about not just your visitor, but their relationship to your products. Use that and you’ll connect more visitors with the content that matters.

Madeline Moran

About Madeline Moran

Madeline is the Marketing Assistant for SoloSegment, an AI fueled software company that makes website conversions easier through personalized content recommendation.

Companies that avoid change management, eventually change management

Digital transformation is all around us–no company can escape. Most companies recognize this, and focus on managing the change in an effective way. But then there are others that think they can avoid digital.

I have been in meetings with clients in which I patiently explained all the forces buffeting their business and what they needed to do to at least cope. (They weren’t ready to compete.) And, on many occasions, I heard excuse after excuse for why they can’t make the needed changes.

My favorite was the time that the manager leaned back in his chair and said, “We understand what you are saying, but it’s just not in our DNA.” I leaned forward and reminded them, “You know that your company can get new DNA, right?”

Six months later, I heard that the manager was let go. When companies avoid change management, eventually they change management.

Don’t let this happen to you. Maybe you think you can ride this out. Maybe you think that digital is coming. It’s not coming. It arrived quite a while ago. If you think digital is coming, you are going.

Instead of waiting to get disruption, you should be figuring out how you can disrupt. I especially see this change avoidance in my largest clients. Instead of trying to avoid the changes, it’s time to embrace them. (Give them a big hug.)

Big companies fail to realize that they have an advantage in digital that upstarts lack–data.

AI has changed the game–large companies are sitting on gobs of data that AI can analyze to find patterns that unlock huge return on investment.

Instead of letting that data lay fallow, it’s time to start using it to unlock the value that AI can bring. To do that, you need to change.

Change, or get changed out. Your choice.

If you’re ready to take the plunge, check out my workshop in June on using analytics to increase conversions at the Marketing Analytics Summit.

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.

SearchChat Podcast: Making Data-Driven Marketing More Human

It’s time for marketers to put humanity back in their marketing practices. Today for SearchChat, Steve Zakur and I discuss first whether you should be worried about government regulation. It seems some marketers have their head in the sand that it will never be an issue, others have their “paranoid” dial turned up to 13. People who have been giving away their data for free are tired of being abused. There’s an unease and distrust around privacy because that trust has been repeatedly violated. Is it the end of data-driven marketing, or does marketing need to get smarter?

We also talk about how White Hat vs Black hat isn’t just for SEO. Think about data usage. When you use personal data, are you trying to game the system or are you providing a benefit? It comes down to asking what the person would think about it, and if they are benefiting.

Meanwhile, we’re rolling our eyes at Zuckerberg’s latest take on Facebook and data privacy. Maybe Facebook doesn’t need the government to tell them how to better regulate — they need to better self-regulate. Has Facebook even earned a seat at the table?

Lastly, In Marketing Charts, B2B marketing leaders point out faults in the marketing message they get. All this and more, coming to you on SearchChat.

0:00 Intro

1:55 Government regulation — is it a threat to data-driven marketing?

7:10 Humanize data-driven marketing

15:07 The disingenuity of Zuckerberg’s Op-Ed

20:40 What content do B2B leaders find important?

27:25 Outtro

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. If you think we might have the answer to your conversion problems, feel free to connect with us.

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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.

The Time is Now: Getting to Your Goals

With less than thirty days to go in the quarter, my mind returns to the business goals we set a few months ago. Some of those OKRs were related to organizational capabilities but the ones that are top of mind relate to pipeline progression and sales. This quarter. Next quarter. You probably have your own metrics that you’re tracking. So what do you do if things aren’t going right?

As a relatively new company we’re still gathering enough data to reliably predict the trends in some places. We’ve made significant investments in getting the right data — we’re disciplined CRM users, we track our marketing activities, and we instrument our platform so we get feedback on utilization. The key is not the data itself but how you put it to work running the business.

I was speaking to a digital marketing leader at a publishing company last week. He was talking about how they’re applying advanced text analytics (embeddings for you geeks out there) to help them with content findability. With tens of millions of documents, they’ve got a fairly unique challenge that is defying traditional search techniques.

One of his challengers is that they don’t have a reliable measure of success for his area. We’re going to talk more about that and see if we can help to set them up for success in the future.

Chicken meet egg

With performance being top of mind I wondered to myself about his ability to demonstrate achievements in this quarter and beyond. I also wondered what I’d do in his place if I were looking forward and trying to build a performance management system that makes sense. That will move the ball downfield. It’s easy to succumb to the desire to work on this next quarter. That’s the wrong instinct. Now is the time. Next quarter will be over before you know it.

There are four things I’d do.

1. In-quarter demonstration of value

No matter how rudimentary your measurement portfolio, you probably have a sense of what success looks like and where your most obvious problems lay.  Find your highest-odds areas of success and go look at that, now. Is there something you can do this week that will change things next week?

The experiment can be modest and half-baked. But it will allow you to demonstrate that you’re taking the issue seriously, and have a bias for action. It may also slightly improve things.

I often recommend people start where they have friends. You know these people. Sometimes they are actually friends, but more often than not they’re the ones who simply nodded in agreement while others were shaking their heads. These are your lab partners.

2. Convene the experts

Whether it’s people within your department, elsewhere in the org or a vendor, you need to demonstrate that you’re able to track progress. This means metrics.

This work will arc into next quarter but by taking the reins this quarter you demonstrate that the measurement gap has both importance and urgency.

Resist the entreaties of some experts that the measurements already exist in some analytics system. That’s Holy Grail talk. If it were there you’d have found it. Someone else would already be using it.

The one thing you might have is data that could be constructed into metrics. Be open to that serendipity but don’t bet on it.

3. Establish a replicable management system

Demonstrating that you’ve got things under control usually requires not only measurements but a feedback and correction mechanism.

This is team sport. Who are the people who are going to enable your success? What organizations are going to be blockers? Who is the person who has the skills to run this thing?

This is another area where your friends can help. Make sure you have allies with you at the table. It’s hard to do this alone.

4. Communicate

Talk to your boss, your peers and those outside you team about what you’re trying to achieve. Create a framework that is clear and concise. Can you fit it on one chart?

Also, don’t forget to listen aggressively while you’re communicating. Part of team sport is knowing the other players well and being able to respond to their ideas. The sum is greater than the parts.

Today

Today is when this starts. Clear your calendar. Get moving. Knowing that a deadline looming sharpens the mind. Yes, everyone else is focused on their goals when deadlines loom, but you’d be surprised how generous people can be. Find them. Get moving. Today. Connect with us to get help along the journey.

Post originally published 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.

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.

Will AI Kill Emotion in Marketing?

Artificial intelligence is a huge buzzword across marketing right now, with over 60% of CEOs saying AI will have a larger impact on their businesses than the internet. Let that soak in for a moment. A larger impact than the internet. ‘Cause, y’know, that’s been a non-event over the last couple decades.

Of course, I’ve talked with a number of marketers who worry that this shift will make them obsolete — that once the machines are in charge, their creativity and passion and emotion will take a back seat to algorithms, to math, to machines.

But is this true? Will AI kill emotion in marketing?

Let’s get the obvious answer out of the way. No, AI does not kill emotion in marketing. Not even close. Suggesting that artificial intelligence kills emotion in marketing is like claiming email, or the internet, or television or whatever technology came before or will emerge in the future kills emotion in marketing. Because marketing is about connecting with customers. And customers, in pretty much every case that I’ve run into across my career, are, y’know, people. And people are emotional. Always.

In fact, I’d argue most marketing, most sales, depends on emotion. IBM famously used to close sales with technology leaders by reminding them, “No one ever got fired for buying IBM.” If that’s not an emotional sell, I don’t know what is.

Instead, here’s what artificial intelligence will do — and in many cases, is doing already. AI does a great job of content recognition and recommendation. My friends at SoloSegment have worked with one client to expose the right content to around 20,000 additional customers every month. These are customers who knew what they wanted, were well along the way on their customer journey, and still were failing to find the information they were looking for on the client site. Even if each of those customers only convert about 1% of the time, that’s two hundred additional conversions — 200 additional sales opportunities — every single month. That’s incredibly powerful.

That effect is even more powerful when combined with the kinds of emotionally-resonant content that great marketers know how to produce.

AI can also help marketers process huge amounts of data. In fact, artificial intelligence often requires large data sets to learn how to provide the best value to marketers. The upside is that it makes understanding that data quite a bit easier. You know why you haven’t heard folks talking as much about “big data” over the last couple years? Because, as a friend of mine always says, AI makes big data little. And better still, most marketers don’t like spending their time digging into data. They’d rather spend their time focused on customers. That’s a Good Thing™. But the algorithms can process the data about what your customers do, what they care about, what motivates them to guide you to deeper understanding of the people you’re trying to connect with. Let the machines do what they’re good at. And that will let you focus on what you’re good at: Emotion. Passion. People.

Let’s be clear, AI isn’t going away anytime soon. But neither are people. The marketers who will achieve the greatest success in the coming years are those who know how to harness the power of artificial intelligence and pair it with a deep appreciation for people, for emotion, for passion. It’s not “AI or emotion.” It’s “AI and emotion.” It’s technology and people. It’s logic and passion.

AI continues to dramatically shape marketing. But so will the creative choices you make as a marketing professional. Use it to better understand your customers, to better connect customers with the content that matters to them, and to continue to deliver emotionally-resonant, customer-focused messages. Who knows? You might just learn to love it. And that’s an emotion we can all use more of, today and every day.

Fell in love with the idea of using AI to shape your marketing? Connect with us to learn how to increase conversions, fast.

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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.