Tag Archive | "Data"

How Palo Alto Networks Blocks 30,000 New Pieces of Malware Daily Via AI, Machine Learning, and Big Data

“The platform we have uses big data analytics and machine learning in the cloud to process and find all of the unknown malware, make it known and be able to block it,” says Scott Stevens, SVP, Global  Systems Engineering at Palo Alto Networks. “We find 20-30 thousand brand new pieces of malware every day. We’re analyzing millions and millions of files every day to figure out which ones are malicious. Once we know, within five minutes we’re updating the security posture for all of our connected security devices globally.”

Scott Stevens, SVP, Global  Systems Engineering at Palo Alto Networks, discusses how the company uses AI, machine learning, and big data to find and block malware for its customers in an interview with Jeff Frick of theCUBE which is covering RSA Conference 2019 in San Francisco:

We Find 20-30 Thousand New Pieces of Malware Every Day

There are two ways to think about artificial intelligence, machine learning, and big data analytics. The first is if we’re looking at how are we dealing with malware and finding unknown malware and blocking it, we’ve been doing that for years. The platform we have uses big data analytics and machine learning in the cloud to process and find all of the unknown malware, make it known and be able to block it.

We find 20-30 thousand brand new pieces of malware every day. We’re analyzing millions and millions of files every day to figure out which ones are malicious. Once we know, within five minutes we’re updating the security posture for all of our connected security devices globally.

Whether it’s endpoint software or it’s our inline next gen firewalls we’re updating all of our signatures so that the unknown is now known and the known can be blocked. That’s whether we’re watching to block the malware coming in or the command-and-control that’s using via DNS and URL to communicate and start whatever it’s going to do. You mentioned crypto lockers and there are all kinds of things that can happen. That’s one vector of using AI NML to prevent the ability for these attacks to succeed.

Machine Learning Uses Data Lake to Discover Malware

The other side of it is how do we then take some of the knowledge and the lessons we’ve learned for what we’ve been doing now for many years in discovering malware and apply that same AI NML locally to that customer so that they can detect very creative attacks very and evasive attacks or that insider threat that employee who’s behaving inappropriately but quietly.

We’ve announced over the last week what we call the cortex XDR set of offerings. That involves allowing the customer to build an aggregated data lake which uses the Zero Trust framework which tells us how to segment and also puts sensors in all the places of the network. This includes both network sensors an endpoint as we look at security the endpoint as well as the network links. Using those together we’re able to stitch those logs together in a data lake that machine learning can now be applied to on a customer by customer basis.

Maybe somebody was able to evade because they’re very creative or that insider threat again who isn’t breaking security rules but they’re being evasive. We can now find them through machine learning. The cool thing about Zero Trust is the prevention architecture that we needed for Zero Trust becomes the sensor architecture for this machine learning engine. You get dual purpose use out of the architecture of Zero Trust to solve both the in-line prevention and the response architecture that you need.

How Palo Alto Networks Blocks 30,000 New Pieces of Malware Daily

>> Read a companion piece to this article here:

Zero Trust Focuses On the Data That’s Key to Your Business

The post How Palo Alto Networks Blocks 30,000 New Pieces of Malware Daily Via AI, Machine Learning, and Big Data appeared first on WebProNews.

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Zero Trust Focuses On the Data That’s Key to Your Business

“The fundamental way you look at Zero Trust is it’s an architectural approach to how do you secure your network focused on what’s most important,” says Scott Stevens, SVP, Global  Systems Engineering at Palo Alto Networks. “You focus on the data that’s key to your business. You build your security framework from the data out.”

Scott Stevens, SVP, Global  Systems Engineering at Palo Alto Networks, discusses Zero Trust in an interview with Jeff Frick of theCUBE which is covering RSA Conference 2019 in San Francisco:

Zero Trust Focuses On the Data That’s Key to Your Business

We’ve been working with Forrester for about six years now looking at Zero Trust architecture. The fundamental way you look at Zero Trust is it’s a an architectural approach to how do you secure your network focused on what’s most important. You focus on the data that’s key to your business. You build your security framework from the data out. There are all kinds of buzzword bingo we can play about what Zero Trust means, but what it allows us to do is to create the right segmentation strategy starting in the data center of the cloud and moving back towards those accessing the data and how you segment and control that traffic.

Fundamentally what we’re dealing with in security are two big problems that we have. First are credential based attacks. Do we have somebody with stolen credentials in the network stealing our data? Or do we have an insider who has credentials but they’re malicious where they’re actually stealing content from the company? The second big problem is software based attacks, malware exploits scripts. How do we segment the network where we can enforce user behavior and we can watch for malicious software so we can prevent both of those occurrences through one architectural framework? I think Zero Trust gives us that template building block on how we build out those networks because everybody’s enterprise network is a little bit different.

You Need To Start With What’s Most Important.

We have to build those things together. On the Palo Alto Networks side what we do is Layer 7 enforcement based on identity. Based on who the user is and what their rights are we are able to control what they are allowed access to or what they’re not allowed access to. Of course, if you’ve got a malicious insider or somebody that’s logged in with stolen credentials we can prevent them from doing what they’re not allowed to do. Working here with Forescout, we’ve done a lot of really good integration with them on that identity mapping construct. They help us understand all the identities and all the devices in the network so we can then map that to that user posture and control at Layer 7 what they’re allowed to do or not allowed to do.

You need to start with what’s most important. Clouds and data centers as a starting point are generally the same. How we segment is actually the same. Sometimes we think that clouds are are more difficult to secure than data centers, but they are the same basically. We’ve got north-south traffic, we have east-west traffic. How do we inspect and how do we segment that? How do we focus on what’s the most important critical data to their business? If we stratify their data sets and their applications that access that data and then move down we may have 50 percent of the applications in their cloud or data center that we don’t micro segment at all because they’re not critical to the business. They’re useful to the employees, but if something goes wrong they’re, no big deal and no impact to the business.

Micro segmentation isn’t just a conversation of where we have to do things but it’s a conversation contextually in terms of what’s relevant and where is it important to do that and then where do you do a much less robust job? You always have to have inspection and visibility, but there are parts of your network where you’re going to be somewhat passive about it and there are parts of your network that you are going to be very aggressive. These include multi-factor authentication, tight user identity mapping, how do we watch for malware, how do we watch for exploits, all of the different aspects.

Zero Trust Focuses On the Data That’s Key to Your Business

>> Read a companion piece to this article here:

How Palo Alto Networks Blocks 30,000 New Pieces of Malware Daily Via AI, Machine Learning, and Big Data

The post Zero Trust Focuses On the Data That’s Key to Your Business appeared first on WebProNews.

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Make sense of your data with these essential keyword segments

Posted by TheMozTeam

This blog post was originally published on the STAT blog.


The first step to getting the most out of your SERP data is smart keyword segmentation — it surfaces targeted insights that will help you make data-driven decisions.

But knowing what to segment can feel daunting, especially when you’re working with thousands of keywords. That’s why we’re arming you with a handful of must-have tags.

Follow along as we walk through the different kinds of segments in STAT, how to create them, and which tags you’ll want to get started with. You’ll be a fanciful segment connoisseur by the time we’re through!

Segmentation in STAT

In STAT, keyword segments are called “tags” and come as two different types: standard or dynamic.

Standard tags are best used when you want to keep specific keywords grouped together because of shared characteristics — like term (brand, product type, etc), location, or device. Standard tags are static, so the keywords that populate those segments won’t change unless you manually add or remove them.

Dynamic tags, on the other hand, are a fancier kind of tag based on filter criteria. Just like a smart playlist, dynamic tags automatically populate with all of the keywords that meet said criteria, such as keywords with a search volume over 500 that rank on page one. This means that the keywords in a dynamic tag aren’t forever — they’ll filter in and out depending on the criteria you’ve set.

How to create a keyword segment

Tags are created in a few easy steps. At the Site level, pop over to the Keywords tab, click the down arrow on any table column header, and then select Filter keywords. From there, you can select the pre-populated options or enter your own metrics for a choose-your-own-filter adventure.

Once your filters are in place, simply click Tag All Filtered Keywords, enter a new tag name, and then pick the tag type best suited to your needs — standard or dynamic — and voila! You’ve created your very own segment.

Segments to get you started

Now that you know how to set up a tag, it’s time to explore some of the different segments you can implement and the filter criteria you’ll need to apply.

Rank and rank movement

Tracking your rank and ranking movements with dynamic tags will give you eyeballs on your keyword performance, making it easy to monitor and report on current and historical trends.

There’s a boatload of rank segments you can set up, but here’s just a sampling to get you started:

  • Keywords ranking in position 1–3; this will identify your top performing keywords.
  • Keywords ranking in position 11–15; this will suss out the low-hanging, top of page two fruit in need of a little nudge.
  • Keywords with a rank change of 10 or more (in either direction); this will show you keywords that are slipping off or shooting up the SERP.

Appearance and ownership of SERP features

Whether they’re images, carousels, or news results, SERP features have significantly altered the search landscape. Sometimes they push you down the page and other times, like when you manage to snag one, they can give you a serious leg up on the competition and drive loads more traffic to your site.

Whatever industry-related SERP features that you want to keep apprised of, you can create dynamic tags that show you the prevalence and movement of them within your keyword set. Segment even further for tags that show which keywords own those features and which have fallen short.

Below are a few segments you can set up for featured snippets and local packs.

Featured snippets

Everyone’s favourite SERP feature isn’t going anywhere anytime soon, so it wouldn’t be a bad idea to outfit yourself with a snippet tracking strategy. You can create as many tags as there are snippet options to choose from:

  • Keywords with a featured snippet.
  • Keywords with a paragraph, list, table, and/or carousel snippet.
  • Keywords with an owned paragraph, list, table, and/or carousel snippet.
  • Keywords with an unowned paragraph, list, table, and/or carousel snippet.

The first two will allow you to see over-arching snippet trends, while the last two will chart your ownership progress.

If you want to know the URL that’s won you a snippet, just take a peek at the URL column.

Local packs

If you’re a brick and mortar business, we highly advise creating tags for local packs since they provide a huge opportunity for exposure. These two tags will show you which local packs you have a presence in and which you need to work on

  • Keywords with an owned local pack.
  • Keywords with an unowned local pack.

Want all the juicy data squeezed into a local pack, like who’s showing up and with what URL? We created the Local pack report just for that.

Landing pages, subdomains, and other important URLs

Whether you’re adding new content or implementing link-building strategies around subdomains and landing pages, dynamic tags allow you to track and measure page performance, see whether your searchers are ending up on the pages you want, and match increases in page traffic with specific keywords.

For example, are your informational intent keywords driving traffic to your product pages instead of your blog? To check, a tag that includes your blog URL will pull in each post that ranks for one of your keywords.

Try these three dynamic tags for starters:

  • Keywords ranking for a landing page URL.
  • Keywords ranking for a subdomain URL.
  • Keywords ranking for a blog URL.

Is a page not indexed yet? That’s okay. You can still create a dynamic tag for its URL and keywords will start appearing in that segment when Google finally gets to it.

Location, location, location

Google cares a lot about location and so should you, which is why keyword segments centred around location are essential. You can tag in two ways: by geo-modifier and by geo-location.

For these, it’s better to go with the standard tag as the search term and location are fixed to the keyword.

Geo-modifier

A geo-modifier is the geographical qualifier that searchers manually include in their query — like in [sushi near me]. We advocate for adding various geo-modifiers to your keywords and then incorporating them into your tagging strategy. For instance, you can segment by:

  • Keywords with “in [city]” in them.
  • Keywords with “near me” in them.

The former will show you how you fare for city-wide searches, while the latter will let you see if you’re meeting the needs of searchers looking for nearby options.


Geo-location

Geo-location is where the keyword is being tracked. More tracked locations mean more searchers’ SERPs to sample. And the closer you can get to searchers standing on a street corner, the more accurate those SERPs will be. This is why we strongly recommend you track in multiple pin-point locations in every market you serve.

Once you’ve got your tracking strategy in place, get your segmentation on. You can filter and tag by:

  • Keywords tracked in specific locations; this will let you keep tabs on geographical trends.
  • Keywords tracked in each market; this will allow for market-level research.

Search volume & cost-per-click

Search volume might be a contentious metric thanks to Google’s close variants, but having a decent idea of what it’s up to is better than a complete shot in the dark. We suggest at least two dynamic segments around search volume:

  • Keywords with high search volume; this will show which queries are popular in your industry and have the potential to drive the most traffic.
  • Keywords with low search volume; this can actually help reveal conversion opportunities — remember, long-tail keywords typically have lower search volumes but higher conversion rates.

Tracking the cost-per-click of your keywords will also bring you and your PPC team tonnes of valuable insights — you’ll know if you’re holding the top organic spot for an outrageously high CPC keyword.

As with search volume, tags for high and low CPC should do you just fine. High CPC keywords will show you where the competition is the fiercest, while low CPC keywords will surface your easiest point of entry into the paid game — queries you can optimize for with less of a fight.

Device type

From screen size to indexing, desktop and smartphones produce substantially different SERPs from one another, making it essential to track them separately. So, filter and tag for:

  • Keywords tracked on a desktop.
  • Keywords tracked on a smartphone.

Similar to your location segments, it’s best to use the standard tag here.

Go crazy with multiple filters

We’ve shown you some really high-level segments, but you can actually filter down your keywords even further. In other words, you can get extra fancy and add multiple filters to a single tag. Go as far as high search volume, branded keywords triggering paragraph featured snippets that you own for smartphone searchers in the downtown core. Phew!

Want to make talk shop about segmentation or see dynamic tags in action? Say hello (don’t be shy) and request a demo.

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4 Ways to Improve Your Data Hygiene – Whiteboard Friday

Posted by DiTomaso

We base so much of our livelihood on good data, but managing that data properly is a task in and of itself. In this week’s Whiteboard Friday, Dana DiTomaso shares why you need to keep your data clean and some of the top things to watch out for.

Click on the whiteboard image above to open a high resolution version in a new tab!

Video Transcription

Hi. My name is Dana DiTomaso. I am President and partner at Kick Point. We’re a digital marketing agency, based in the frozen north of Edmonton, Alberta. So today I’m going to be talking to you about data hygiene.

What I mean by that is the stuff that we see every single time we start working with a new client this stuff is always messed up. Sometimes it’s one of these four things. Sometimes it’s all four, or sometimes there are extra things. So I’m going to cover this stuff today in the hopes that perhaps the next time we get a profile from someone it is not quite as bad, or if you look at these things and see how bad it is, definitely start sitting down and cleaning this stuff up.

1. Filters

So what we’re going to start with first are filters. By filters, I’m talking about analytics here, specifically Google Analytics. When go you into the admin of Google Analytics, there’s a section called Filters. There’s a section on the left, which is all the filters for everything in that account, and then there’s a section for each view for filters. Filters help you exclude or include specific traffic based on a set of parameters.

Filter out office, home office, and agency traffic

So usually what we’ll find is one Analytics property for your website, and it has one view, which is all website data which is the default that Analytics gives you, but then there are no filters, which means that you’re not excluding things like office traffic, your internal people visiting the website, or home office. If you have a bunch of people who work from home, get their IP addresses, exclude them from this because you don’t necessarily want your internal traffic mucking up things like conversions, especially if you’re doing stuff like checking your own forms.

You haven’t had a lead in a while and maybe you fill out the form to make sure it’s working. You don’t want that coming in as a conversion and then screwing up your data, especially if you’re a low-volume website. If you have a million hits a day, then maybe this isn’t a problem for you. But if you’re like the rest of us and don’t necessarily have that much traffic, something like this can be a big problem in terms of the volume of traffic you see. Then agency traffic as well.

So agencies, please make sure that you’re filtering out your own traffic. Again things like your web developer, some contractor you worked with briefly, really make sure you’re filtering out all that stuff because you don’t want that polluting your main profile.

Create a test and staging view

The other thing that I recommend is creating what we call a test and staging view. Usually in our Analytics profiles, we’ll have three different views. One we call master, and that’s the view that has all these filters applied to it.

So you’re only seeing the traffic that isn’t you. It’s the customers, people visiting your website, the real people, not your office people. Then the second view we call test and staging. So this is just your staging server, which is really nice. For example, if you have a different URL for your staging server, which you should, then you can just include that traffic. Then if you’re making enhancements to the site or you upgraded your WordPress instance and you want to make sure that your goals are still firing correctly, you can do all that and see that it’s working in the test and staging view without polluting your main view.

Test on a second property

That’s really helpful. Then the third thing is make sure to test on a second property. This is easy to do with Google Tag Manager. What we’ll have set up in most of our Google Tag Manager accounts is we’ll have our usual analytics and most of the stuff goes to there. But then if we’re testing something new, like say the content consumption metric we started putting out this summer, then we want to make sure we set up a second Analytics view and we put the test, the new stuff that we’re trying over to the second Analytics property, not view.

So you have two different Analytics properties. One is your main property. This is where all the regular stuff goes. Then you have a second property, which is where you test things out, and this is really helpful to make sure that you’re not going to screw something up accidentally when you’re trying out some crazy new thing like content consumption, which can totally happen and has definitely happened as we were testing the product. You don’t want to pollute your main data with something different that you’re trying out.

So send something to a second property. You do this for websites. You always have a staging and a live. So why wouldn’t you do this for your analytics, where you have a staging and a live? So definitely consider setting up a second property.

2. Time zones

The next thing that we have a lot of problems with are time zones. Here’s what happens.

Let’s say your website, basic install of WordPress and you didn’t change the time zone in WordPress, so it’s set to UTM. That’s the default in WordPress unless you change it. So now you’ve got your data for your website saying it’s UTM. Then let’s say your marketing team is on the East Coast, so they’ve got all of their tools set to Eastern time. Then your sales team is on the West Coast, so all of their tools are set to Pacific time.

So you can end up with a situation where let’s say, for example, you’ve got a website where you’re using a form plugin for WordPress. Then when someone submits a form, it’s recorded on your website, but then that data also gets pushed over to your sales CRM. So now your website is saying that this number of leads came in on this day, because it’s in UTM mode. Well, the day ended, or it hasn’t started yet, and now you’ve got Eastern, which is when your analytics tools are recording the number of leads.

But then the third wrinkle is then you have Salesforce or HubSpot or whatever your CRM is now recording Pacific time. So that means that you’ve got this huge gap of who knows when this stuff happened, and your data will never line up. This is incredibly frustrating, especially if you’re trying to diagnose why, for example, I’m submitting a form, but I’m not seeing the lead, or if you’ve got other data hygiene issues, you can’t match up the data and that’s because you have different time zones.

So definitely check the time zones of every product you use –website, CRM, analytics, ads, all of it. If it has a time zone, pick one, stick with it. That’s your canonical time zone. It will save you so many headaches down the road, trust me.

3. Attribution

The next thing is attribution. Attribution is a whole other lecture in and of itself, beyond what I’m talking about here today.

Different tools have different ways of showing attribution

But what I find frustrating about attribution is that every tool has its own little special way of doing it. Analytics is like the last non-direct click. That’s great. Ads says, well, maybe we’ll attribute it, maybe we won’t. If you went to the site a week ago, maybe we’ll call it a view-through conversion. Who knows what they’re going to call it? Then Facebook has a completely different attribution window.

You can use a tool, such as Supermetrics, to change the attribution window. But if you don’t understand what the default attribution window is in the first place, you’re just going to make things harder for yourself. Then there’s HubSpot, which says the very first touch is what matters, and so, of course, HubSpot will never agree with Analytics and so on. Every tool has its own little special sauce and how they do attribution. So pick a source of truth.

Pick your source of truth

This is the best thing to do is just say, “You know what? I trust this tool the most.” Then that is your source of truth. Do not try to get this source of truth to match up with that source of truth. You will go insane. You do have to make sure that you are at least knowing that things like your time zones are clear so that’s all set.

Be honest about limitations

But then after that, really it’s just making sure that you’re being honest about your limitations.

Know where things are necessarily going to fall down, and that’s okay, but at least you’ve got this source of truth that you at least can trust. That’s the most important thing with attribution. Make sure to spend the time and read how each tool handles attribution so when someone comes to you and says, “Well, I see that we got 300 visits from this ad campaign, but in Facebook it says we got 6,000.

Why is that? You have an answer. That might be a little bit of an extreme example, but I mean I’ve seen weirder things with Facebook attribution versus Analytics attribution. I’ve even talked about stuff like Mixpanel and Kissmetrics. Every tool has its own little special way of recording attributions. It’s never the same as anyone else’s. We don’t have a standard in the industry of how this stuff works, so make sure you understand these pieces.

4. Interactions

Then the last thing are what I call interactions. The biggest thing that I find that people do wrong here is in Google Tag Manager it gives you a lot of rope, which you can hang yourself with if you’re not careful.

GTM interactive hits

One of the biggest things is what we call an interactive hit versus a non-interactive hit. So let’s say in Google Tag Manager you have a scroll depth.

You want to see how far down the page people scroll. At 25%, 50%, 75%, and 100%, it will send off an alert and say this is how far down they scrolled on the page. Well, the thing is that you can also make that interactive. So if somebody scrolls down the page 25%, you can say, well, that’s an interactive hit, which means that person is no longer bounced, because it’s counting an interaction, which for your setup might be great.

Gaming bounce rate

But what I’ve seen are unscrupulous agencies who come in and say if the person scrolls 2% of the way down the page, now that’s an interactive hit. Suddenly the client’s bounce rate goes down from say 80% to 3%, and they think, “Wow, this agency is amazing.” They’re not amazing. They’re lying. This is where Google Tag Manager can really manipulate your bounce rate. So be careful when you’re using interactive hits.

Absolutely, maybe it’s totally fair that if someone is reading your content, they might just read that one page and then hit the back button and go back out. It’s totally fair to use something like scroll depth or a certain piece of the content entering the user’s view port, that that would be interactive. But that doesn’t mean that everything should be interactive. So just dial it back on the interactions that you’re using, or at least make smart decisions about the interactions that you choose to use. So you can game your bounce rate for that.

Goal setup

Then goal setup as well, that’s a big problem. A lot of people by default maybe they have destination goals set up in Analytics because they don’t know how to set up event-based goals. But what we find happens is by destination goal, I mean you filled out the form, you got to a thank you page, and you’re recording views of that thank you page as goals, which yes, that’s one way to do it.

But the problem is that a lot of people, who aren’t super great at interneting, will bookmark that page or they’ll keep coming back to it again and again because maybe you put some really useful information on your thank you page, which is what you should do, except that means that people keep visiting it again and again without actually filling out the form. So now your conversion rate is all messed up because you’re basing it on destination, not on the actual action of the form being submitted.

So be careful on how you set up goals, because that can also really game the way you’re looking at your data.

Ad blockers

Ad blockers could be anywhere from 2% to 10% of your audience depending upon how technically sophisticated your visitors are. So you’ll end up in situations where you have a form fill, you have no corresponding visit to match with that form fill.

It just goes into an attribution black hole. But they did fill out the form, so at least you got their data, but you have no idea where they came from. Again, that’s going to be okay. So definitely think about the percentage of your visitors, based on you and your audience, who probably have an ad blocker installed and make sure you’re comfortable with that level of error in your data. That’s just the internet, and ad blockers are getting more and more popular.

Stuff like Apple is changing the way that they do tracking. So definitely make sure that you understand these pieces and you’re really thinking about that when you’re looking at your data. Again, these numbers may never 100% match up. That’s okay. You can’t measure everything. Sorry.

Bonus: Audit!

Then the last thing I really want you to think about — this is the bonus tip — audit regularly.

So at least once a year, go through all the different stuff that I’ve covered in this video and make sure that nothing has changed or updated, you don’t have some secret, exciting new tracking code that somebody added in and then forgot because you were trying out a trial of this product and you tossed it on, and it’s been running for a year even though the trial expired nine months ago. So definitely make sure that you’re running the stuff that you should be running and doing an audit at least on an yearly basis.

If you’re busy and you have a lot of different visitors to your website, it’s a pretty high-volume property, maybe monthly or quarterly would be a better interval, but at least once a year go through and make sure that everything that’s there is supposed to be there, because that will save you headaches when you look at trying to compare year-over-year and realize that something horrible has been going on for the last nine months and all of your data is trash. We really don’t want to have that happen.

So I hope these tips are helpful. Get to know your data a little bit better. It will like you for it. Thanks.

Video transcription by Speechpad.com

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How to Stop Drowning in Data and Begin Using Your Metrics Wisely

Digital marketers have a problem: We’ve got too much data. It sounds like a ridiculous complaint coming from a data…

The post How to Stop Drowning in Data and Begin Using Your Metrics Wisely appeared first on Copyblogger.


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My Five Greatest Mistakes as A Leader: 30 years of painful data (that might help you)

For the leader, sometimes the most important data is derived from a source that evades our metrics platforms. Indeed, such data can only be gleaned through brutal self-confrontation.
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SearchCap: Reporting delays in Google Search Console, navigate in search & structure data

Below is what happened in search today, as reported on Search Engine Land and from other places across the web.



Please visit Search Engine Land for the full article.


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Google updates Shopping Insights for product search data and trends

Marketers and retailers can get more comparative brand data with the latest update.



Please visit Search Engine Land for the full article.


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How to Create a Local Marketing Results Dashboard in Google Data Studio – Whiteboard Friday

Posted by DiTomaso

Showing clients that you’re making them money is one of the most important things you can communicate to them, but it’s tough to know how to present your results in a way they can easily understand. That’s where Google Data Studio comes in. In this week’s edition of Whiteboard Friday, our friend Dana DiTomaso shares how to create a client-friendly local marketing results dashboard in Google Data Studio from start to finish.

Click on the whiteboard image above to open a high-resolution version in a new tab!

Video Transcription

Hi, Moz fans. My name is Dana DiTomaso. I’m President and partner of Kick Point. We’re a digital marketing agency way up in the frozen north of Edmonton, Alberta. We work with a lot of local businesses, both in Edmonton and around the world, and small local businesses usually have the same questions when it comes to reporting.

Are we making money?

What I’m going to share with you today is our local marketing dashboard that we share with clients. We build this in Google Data Studio because we love Google Data Studio. If you haven’t watched my Whiteboard Friday yet on how to do formulas in Google Data Studio, I recommend you hit Pause right now, go back and watch that, and then come back to this because I am going to talk about what happened there a little bit in this video.

The Google Data Studio dashboard

This is a Google Data Studio dashboard which I’ve tried to represent in the medium of whiteboard as best as I could. Picture it being a little bit better design than my left-handedness can represent on a whiteboard, but you get the idea. Every local business wants to know, “Are we making money?” This is the big thing that people care about, and really every business cares about making money. Even charities, for example: money is important obviously because that’s what keeps the lights on, but there’s also perhaps a mission that they have.

But they still want to know: Are people filling out our donation form? Are people contacting us? These are important things for every business, organization, not-for-profit, whatever to understand and know. What we’ve tried to do in this dashboard is really boil it down to the absolute basics, one thing you can look at, see a couple of data points, know whether things are good or things are bad.

Are people contacting you?

Let’s start with this up here. The first thing is: Are people contacting you? Now you can break this out into separate columns. You can do phone calls and emails for example. Some of our clients prefer that. Some clients just want one mashed up number. So we’ll take the number of calls that people are getting.

If you’re using a call tracking tool, such as CallRail, you can import this in here. Emails, for example, or forms, just add it all together and then you have one single number of the number of times people contacted you. Usually this is a way bigger number than people think it is, which is also kind of cool.

Are people taking the action you want them to take?

The next thing is: Are people doing the thing that you want them to do? This is really going to decide on what’s meaningful to the client.

For example, if you have a client, again thinking about a charity, how many people filled out your donation form, your online donation form? For a psychologist client of ours, how many people booked an appointment? For a client of ours who offers property management, how many people booked a viewing of a property? What is the thing you want them to do? If they have online e-commerce, for example, then maybe this is how many sales did you have.

Maybe this will be two different things — people walking into the store versus sales. We’ve also represented in this field if a person has a people counter in their store, then we would pull that people counter data into here. Usually we can get the people counter data in a Google sheet and then we can pull it into Data Studio. It’s not the prettiest thing in the world, but it certainly represents all their data in one place, which is really the whole point of why we do these dashboards.

Where did visitors com from, and where are your customers coming from?

People contacting you, people doing the thing you want them to do, those are the two major metrics. Then we do have a little bit deeper further down. On this side here we start with: Where did visitors come from, and where are your customers coming from? Because they’re really two different things, right? Not every visitor to the website is going to become a customer. We all know that. No one has a 100% conversion rate, and if you do, you should just retire.

Filling out the dashboard

We really need to differentiate between the two. In this case we’re looking at channel, and there probably is a better word for channel. We’re always trying to think about, “What would clients call this?” But I feel like clients are kind of aware of the word “channel” and that’s how they’re getting there. But then the next column, by default this would be called users or sessions. Both of those are kind of cruddy. You can rename fields in Data Studio, and we can call this the number of people, for example, because that’s what it is.

Then you would use the users as the metric, and you would just call it number of people instead of users, because personally I hate the word “users.” It really boils down the humanity of a person to a user metric. Users are terrible. Call them people or visitors at least. Then unfortunately, in Data Studio, when you do a comparison field, you cannot rename and call it comparison. It does this nice percentage delta, which I hate.

It’s just like a programmer clearly came up with this. But for now, we have to deal with it. Although by the time this video comes out, maybe it will be something better, and then I can go back and correct myself in the comments. But for now it’s percentage delta. Then goal percentage and then again delta. They can sort by any of these columns in Data Studio, and it’s real live data.

Put a time period on this, and people can pick whatever time period they want and then they can look at this data as much as they want, which is delightful. If you’re not delivering great results, it may be a little terrifying for you, but really you shouldn’t be hiding that anyway, right? Like if things aren’t going well, be honest about it. That’s another talk for another time. But start with this kind of chart. Then on the other side, are you showing up on Google Maps?

We use the Supermetrics Google My Business plug-in to grab this kind of information. We hook it into the customer’s Google Maps account. Then we’re looking at branded searches and unbranded searches and how many times they came up in the map pack. Usually we’ll have a little explanation here. This is how many times you came up in the map pack and search results as well as Google Maps searches, because it’s all mashed in together.

Then what happens when they find you? So number of direction requests, number of website visits, number of phone calls. Now the tricky thing is phone calls here may be captured in phone calls here. You may not want to add these two pieces of data or just keep this off on its own separately, depending upon how your setup is. You could be using a tracking number, for example, in your Google My Business listing and that therefore would be captured up here.

Really just try to be honest about where that data comes from instead of double counting. You don’t want to have that happen. The last thing is if a client has messages set up, then you can pull that message information as well.

Tell your clients what to do

Then at the very bottom of the report we have a couple of columns, and usually this is a longer chart and this is shorter, so we have room down here to do this. Obviously, my drawing skills are not as good as as aligning things in Data Studio, so forgive me.

But we tell them what to do. Usually when we work with local clients, they can’t necessarily afford a monthly retainer to do stuff for clients forever. Instead, we tell them, “Here’s what you have to do this month.Here’s what you have to do next month. Hey, did you remember you’re supposed to be blogging?” That sort of thing. Just put it in here, because clients are looking at results, but they often forget the things that may get them those results. This is a really nice reminder of if you’re not happy with these numbers, maybe you should do these things.

Tell your clients how to use the report

Then the next thing is how to use. This is a good reference because if they only open it say once every couple months, they probably have forgotten how to do the stuff in this report or even things like up at the top make sure to set the time period for example. This is a good reminder of how to do that as well.

Because the report is totally editable by you at any time, you can always go in and change stuff later, and because the client can view the report at any time, they have a dashboard that is extremely useful to them and they don’t need to bug you every single time they want to see a report. It saves you time and money. It saves them time and money. Everybody is happy. Everybody is saving money. I really recommend setting up a really simple dashboard like this for your clients, and I bet you they’ll be impressed.

Thanks so much.

Video transcription by Speechpad.com

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Calculated Fields in Google Data Studio – Whiteboard Friday

Posted by DiTomaso

Google Data Studio is a powerful tool to have in your SEO kit. Knowing how to get the most out of its power begins with understanding how to use calculated fields to apply good old-fashioned math to your data. In this week’s Whiteboard Friday, we’re delighted to welcome guest host Dana DiTomaso as she takes us through how to use calculated fields in Google Data Studio to uncover more value in your data and improve your reports.

Calculated Fields in Google Data Studio

Click on the whiteboard image above to open a high-resolution version in a new tab!


Video Transcription

Hi, Moz fans. I’m Dana DiTomaso, President and partner at Kick Point, and we love Google Data Studio at Kick Point. You may not love Google Data Studio yet, but after you watch this I think you probably will.

One of the first things that you think about Google Data Studio is: Why would I use this? It’s just charts. It’s the same thing I can get in Analytics or a billion other dashboarding tools out there. But one of the things that I really like about Google Data Studio is math. You can do lots of different stuff in Data Studio, and I’m going to go through four of the basic types in Data Studio and then how you can use that to improve your reports, just as you sort of dip your toes into the Google Data Studio pool. What I’ve done here is I have written out a lot of the formulas that you’re going to be using.

The types

It’s a lot of obviously written out formulas, but when you get into Data Studio, you should be able to type these in and they’ll work. Let’s start at the beginning with the types.

  1. Basic math. This is pretty obvious. 1 + 1 = 2. Phone calls plus emails equals this, for example. You can add together different fields.
  2. Transforms. Let’s say people are really bad at writing some things upper case and some things lower case. You have a problem with URLs being written a couple of different ways. You can use a transform to transform upper case into lower case. That’s pretty nice.
  3. Formulas. Formulas is where you’re saying only show this subset of the data. Or how often does this happen? That could be things like the Count function, so count how many times this occurs, for example, and present that as a totally separate metric, which can be really useful for things like when you want to count the number of times an event occurs and then compare that against something else. It can just pull out that kind of data.
  4. Logic. This is the more complex one. If X, then Y. If this happens, then that’s going to happen. There’s a lot of really complex stuff in there. But if you’re just getting started, start with this, and then look at the Google Data Studio documentation. You’ll find some cooler stuff in there.

1. Basic math

Here are some examples of how we use this in our Google Data Studio dashboards. So basic math, one of the things that a lot of people care about is: Are people getting in touch with me?

This is the basics of the reason why we do marketing. Are people getting in touch? So, for example, you can do some basic math and say, “All right. So I know on our website in Google Tag Manager, we have a trigger that fires whenever somebody taps or clicks a MailTo link on the site.” In addition to that, we’re tracking how many people submit a form, as you should.

Instead of reporting these separately, really they’re kind of the same thing. They’re emailing one way or the other. Why don’t we just submit them as one metric? So in that case, you can say grab all the mail to form completions and then grab all the form goal completions, and now you have a total email requests or total requests or whatever you might want to call it. You can do the same thing where it’s like, well, phone calls and emails, does it really matter if they’re in separate buckets?

Just put them all in one. The same thing with the basic math. Just add it all together and then you’ve got one total metric you can present to the client. Here’s how much money we made for you. Boom. That’s a nice one. The next thing — I’m just going to flip over here — is formulas.

2. Formulas

Okay, so formulas, one of the things that I really like doing is looking at your Google Search Console data. This is in Data Studio. You’re going to use Search Console for this, which is a nice data source. We all know Search Console data is not necessarily 100% accurate, but there’s always lots of keyword treasure in there to be found if it’s easy to find, which the Search Console interface isn’t super great.

So you can make a report in Data Studio and say regex match, and so don’t be afraid of regex. I think everyone should learn it. But if you’re not super familiar with it, this is a really easy way to do it. Say, okay, every time a keyword contains why, how, can, what, for example, then those are question searches. You may change it to whatever makes sense for you.

But this is just pulling out that subset of data. Then you can see, so if these are question searches, do we have content that answers that question? No. Maybe this is something we need to think about. Or we’re getting impressions for this. You could filter it and say only show questions searches where our average rank is below 20. Maybe if we improve this content, this is a featured snippet opportunity for us, for example. That’s a real gold mine of data you can play around with.

3. Transforms

The third one is transforms. As I mentioned earlier, this is a really nice way to take Facebook, for example. We had a client who had Facebook in all upper case and Facebook in title case and Facebook in lower case in their sources and mediums, because they were very casual with how they used their UTM codes. We just standardized them all to go to lower, and those are nice text transforms that you can do.

It just makes things look a little bit nicer. I do recommend doing some of this, especially if you have messy data.

4. Logic

Then the big one here. This is logic, and I’m just going to toss over here for a second. Now logic has a lot of different components. What I’m showing you right now is a case when else end transform or logic. We use this to tidy up bad channel data.

So that client that I mentioned, who was just super casual with their UTM tags and they would just put in any old stuff, I think they had retargeting ads as a medium. You can set up channels and whatnot in Google Analytics. But I mean, really, when it comes down to it, not everybody is great at following the rules for UTMs that you’ve set up. Stuff happens.

It’s okay. You can fix it in Data Studio. Especially if you open up Google Analytics and you see that you have this other channel, which I’m sure when we’ve inherited an Analytics account, we take a look at it, and there’s this channel, and it’s just a big bag of crap.

You can go in there and turn that into real, useful, actual channel data that matches up with where it should go. What I’ve got here is a really simple example. This could go on for lines and line and lines. I’ve just included two lines because this whiteboard is only so big.

So you start off by saying case. It is the case when, is the idea when, and then the first line here is source equals direct and medium equals not set or medium none, then direct. So I’m saying, okay, so this is the basics of how direct traffic happens.

If the source is direct and the medium is not set or the medium is none, like if I have no data whatsoever, now it’s direct traffic. Great, that’s basically what Google Analytics does. Nothing fancy is going on here. Now here’s the next thing. In this case, I’m saying now I’m combining a regex match, which we talked about up here, with the case, and so now what I’m saying is when regex match medium, and then I’ve got this here.

Don’t be scared of this. I know it’s regex and maybe you’re not super comfortable with it, but this is pretty elementary stuff, and once you do this, you will feel like a data wizard, I guarantee. The first time I did this I stood up from my computer and said “Yes” the first time it worked. Just play with it. It’s going to be awesome. So you’ve got a little … what’s the thing called? You’ve got a little up arrow thingy there, very bad mediums dollar sign.

What this is saying is that if you’ve got anything in there that’s sort of a weird medium, just write out all the crud that people have put in there over the years, all the weird mediums that totally don’t make any sense at all. Just put it all in there and then you can toss it in a bucket say called paid social. You can do the same thing with referral traffic. Or, for example, this is really useful if a client is saying, “Well, I want to know how this set of affiliate traffic compares to say this set of affiliate traffic,” then you can separate these out into different buckets.

This isn’t just for channel data. I’ve done this, for example, where we were looking at social data and we were comparing NFL teams as an example for another tool, Rival IQ. What I said was, okay, so these teams here are in the AFC East, and these teams are in the AFC West. If I’ve screwed up and I said AFC East and West, please don’t get mad at me in the comments. I promise I play fantasy football. I just don’t remember right now.

But you can combine different areas. This is great for things like sales regions, for example. So North America equals Canada plus the USA plus Mexico, if you’re feeling generous. This is NAFTA politics. It really depends on what you want to do with those sales regions and how your data, what is meaningful for you. That’s the most important thing about this is that you can change this data to be whatever you need it to be to make that reporting so much easier for you.

I mean, Else then, we don’t know if this might actually output. I haven’t tried this myself. If it does, please leave a comment and let me know.

Then you end up with an End. When you’re in Data Studio, when you’re making these calculated formulas, you’ll see right away whether or not it works or not. Just keep trying until you see it happen.

One of the great things about Data Studio is that if it’s right, you’ll see these types of colors, and I’ve used different color whiteboard markers to indicate how it should look. If you see red where you should be seeing black or green where you should be seeing black, for example, then you know you’ve typed in something wrong in your formula. For me, typically I find it’s a misplaced bracket. Just keep an eye on that.

Have fun with Data Studio. One of the great things too is that you can’t mess up your original data when doing calculated fields, so you can go hog wild and it’s not going to mess with the original data. I hope you have a great time in Data Studio. Tell me what you’ve done in the comments, please. Thank you.

Video transcription by Speechpad.com

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