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Whether we’re talking about everyday life, or the world of business platforms – we believe that decisions, big or small, should be made based on data. This forms the crux of our technology – so how does one make effective data-driven decisions regarding customers? How do you innovate the experience, and optimize the content they view and consume? Ultimately, how do you make customers more successful?

There’s been a lot of content structured around these very questions – do a quick Google search and you’ll find a ton of reading material. We had a look at some of these posts and wanted to share how our thoughts – our unique take on the industry of business data, really – differs.

More than anything, you’ll find that online publications believe that high-level plans should be based around collected, factual data. Other publications focus more heavily on data trends and anomalies; another useful tool in determining the next necessary steps needed.

Because trailblazers like being different, we’re not going to focus on any of those notions. With our own unique concepts of success comes our own unique methods to reaching that success – we believe the there are three keys to making powerful data-driven decisions:

Grouping, Comparing, and Sequencing.

Grouping

Grouping is a key step in understanding data – before you even begin going through numbers, it is essential to group your users into sections that can be tracked and measured. If making your customers successful is your primary goal (it’s certainly ours), you must first be able to see which groups of customers are doing what, when they’re doing it, and where it’s happening. This is where specificity becomes crucial – many companies make the mistake of tracking too broadly (weekly or monthly), ultimately missing out on more specific insights about group behaviors. Don’t get us wrong; making high-level groupings can be useful and telling. But without digging into more specific instances, you run the risk of losing customer loyalty by missing more minute analytics buried in the data.

Piggy-backing on the previous paragraph, it’s important to distinguish between broad and specific groupings – high-level grouping includes categories like age, gender, location, and income level. More specific conditions can than be scrutinized for more minute data; like actions, interactions, transactions, customers that purchase multiple items and customers who spend, say, 100 hours browsing the site. Again, these are just examples – there are thousands of specific questions and data points just like these. Further complexities are added when combining specific points with general ones, like: “all women who are over 40 years old who have purchased something more than once via Twitter or Facebook.” Now we’re getting more specific.

Yet the rabbit hole gets deeper. Adding a time-range is one of the quickest ways to analyze specific data and compare patterns that occur during different points throughout the year (particularly useful for online vendors). So on top of the aforementioned example, you could add “in the last 30 days,” or, “within any 30 minute time span.” The latter example showcases our flexibility – you can literally monitor the analytics of a new product only minutes after its release, then compare that data with longer-running stats later. Comparison is a crucial element of making data-driven decisions; so let’s talk about why.

Comparing

At a fundamental level, we make the best decisions by comparing our options – 100% of the time, making a decision means weighing the potential benefits and downfalls of two or more options.

Therefore, comparing two or more things allows us to properly assess the similarities and differences between all of our options and then base our decision on specific data points that come out of that comparison. Now, the most common comparison to make is between the same group of users over different periods of time. For example, we can compare results of a group this week versus last week, or today versus this same day of the week last month, etc. This has proven very useful in making high-level decisions that affect the business and direction of the company.

In the context of achieving successful user experience and customer journeys, however, this comparison becomes even more insightful and revealing when we consider two groups of customers that are specific, yet slightly different.

Let’s look at an example of this notion. Let’s say we’ve grouped our customers into two sections: “California residents over 30-years-old who have made a single purchase in the past week,” and “Texas residents over 30-years-old who have made a single purchase in the past week.” Because most of the parameters are identical, we know to compare the differences in locations. If the results were roughly similar, we could deduce that location has little to do with the performance of this particular hypothetical. This is a simple example, but clearly illustrates how these sorts of analytics can be used to remove or disregard factors that don’t cause impactful change.

Similarly, let’s posit another hypothetical. Let’s make the same comparison, only this time, let’s change the age group – once again, if the results remain similar, we can rule that factor out as well.

Here’s where it gets tricky – let’s take the first example, and hypothetically surmise that the change in location yielded divisive results. This would automatically tell the user that the purchase location is an integral factor in determining the success of the campaign, meaning more questions and analysis should be focused on that particular aspect is not only accurate, but defensible.

The point is that there’s a fine line to walk when grouping your customers – you want to group them specifically, sure, but also make sure to maintain some level of flexibility for the sake of comparison. By continually making nuanced comparisons, you can find the single group property, attribute, or condition that ensures your data-driven decision. Let’s touch on the final key technique needed to make data-driven decisions – sequencing.

Sequencing

Any user event, by default, is defined by the following three required elements:

  • Actor – the user or device that completes an action.
  • Action – something that an actor completes.
  • Timestamp – the point in time when an actor completes the action.

Though these are the three fundamental aspects of any given user event, there are supplemental attributes that sometimes come into play.

Let’s talk about grouping actors. As we discussed previously, actors can be grouped based on specific properties or conditions, then studied over a chosen period of time. As such, the user event timestamp is always referenced for inclusion or exclusion purposes. Put plainly: user events only exist within the specified time range of the comparison – otherwise the results are simply excluded, making for useless data. This is important to keep in mind.

Let’s look at an example: “How many users over the age of 18 have signed up for our newsletter this month?,” is a common and simple question to analyze. Replacing “…this month” with “in the last month” will give us a new set of numbers, and a basis for a fair comparison. This is the quickest way to answer a simple question: have the numbers increased or decreased since last month?

This is fairly standard practice, and though it offers a general sense of direction, it’s also a simple comparison in the world of analytics – there’s more insight to be gained by digging into that timeframe, like user actions, interactions and transactions. Simply put, we now know how much one set of numbers changed in that given time, but we don’t know why.

We can certainly guess, (or derive some theory or hypothesis), and base our decisions on guesses fueled by broad data – though this hardly seems data-driven. Even with a general framework, a guess is still a guess. Luckily, each event has a timestamp, meaning we have the option of laying out each unique event sequentially (hence the term ‘sequencing’). Once the events are laid out in a timeline that makes sense, we can then retroactively rebuild the exact paths and flows our actors took. In other words, we can study their behavior every step of the way, then compare those steps to other actors in a different grouping.

The result? An acute ability to spot patterns that emerge from event sequencing that helps us determine why or who did what, and when and where they did it. Eventually, we can explain and defend our data-driven decisions based on the culmination of these four indicators – which leaves us with how our customers did what they did.

In summary

As you can see, a whole lot of analytical concepts go into making sound, data-driven decisions. Typical methods of gathering and parsing metrics aren’t deep enough, and will likely point you in the right direction but leave you guessing when it times come to make important decisions.

And at the end of the day, that’s what this is all about. Making a data-driven decision is dependent on how users group, sequence, and compare user events – this is the most concrete way to reveal, in detail, all facets of customer actions and interactions. This means that users can ensure their customers have a successful experience, while simultaneously establishing trust and brand loyalty every step of the way. When it comes to data, we want users to stop guessing, and start knowing –  a mantra we repeat at Interana that is music to our ears. Speaking of which, try it for yourself. Turn your team into a true orchestra of productivity and collaborative thought, and hear the music too.

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Knowing How and When Customers Engage and Interact is Critical to Staying Ahead of the Competition

by Alan Fackler16-07-2018

As of today, businesses have 129 days and counting until Black Friday, which takes place on November 23rd. This is a make-or-break date for many retailers, particularly online entities, who will be counting on the revenue from this massive day of commerce to keep the ship afloat as it sails towards the horizons of new yearly sales. Anticipating this event beforehand – as well as many other holiday sales events that happen after – is critical. We’ve seen businesses make the difficult decision to close their doors due to poor Black Friday performance – which, we’ve come to learn, is almost always a result of two things: poor planning, and & a poor understanding of metrics.

Thought Leadership
Are Your Teams Making Decisions Based on Intuition or Data?

by Alan Fackler16-07-2018

Traditional analytical reporting tools simply don’t work. You’re probably employing three or more tools and still can’t get the necessary answers needed to make critical decisions - even after custom coding and queries are deployed to meet the needs of your CEO. Furthermore, business teams across the company have questions, and they expect answers, fast, exactly when they need them. What if you could offer your business teams more than just a single snapshot in time, but an entire movie - a fluid experience - that can be paused (with Blu-ray quality), rewound, rewatched, skipped, and replayed at any point?

Thought Leadership
The Low Cost of Failure

by Maverick Garner05-07-2018

In the weeks since I adopted this effective method of thinking, I find myself exercising more and more (I’m doing more than one push-up a day, for sure). Part of what keeps me motivated is that, at the end of the day, the initial goal is still exceedingly simple: one push-up a day, minimum. So if I find myself tired from a long day at work, or too stressed to push myself physically, I find personal solace in the fact that accomplishing the minimum still means I’m adhering to my daily workout parameters. It’s that dynamic – setting a low cost of failure to gradually increase returns – that influenced the creation of the article in front of you.

Thought Leadership
The Declaration of Analytics Independence

by Maverick Garner22-06-2018

With the Fourth of July holiday just on the horizon, I thought about what our forefathers must have been thinking that led to the decision to declare independence from England. As I imagined what they were experiencing, what they believed, and how those two things were conflicting within their spirits, I started to realize that I, too, was caught up in a similar conflict with regards to the analytics space, specifically analytics.

Thought Leadership
Virtual Gaming World (VGW) Doubles LuckyLand Slots Average Revenue

by Kelly Brieger18-06-2018

VGW, a pioneering online gaming and sweepstakes company, brings the excitement of hitting the jackpot online with LuckyLand Slots. The company has innovated on various digital platforms while incorporating social connections and multiplayer futures throughout its platform. They needed to know more about how customers played, shared, interacted, purchased, and even got frustrated, would be a critical piece of the puzzle as they introduced new features and functionality. Not only would VGW have to be a leader in creating engaging games and social experiences, but they would also need to become experts about their customers. With this drive to deeply understand customer behavior, VGW needed an analytics solution that could convert their raw event data into an intuitive graphical interface, so that everyone in the company could iterate on questions while getting fast answers. Here’s how Interana helped convert VGW’s raw event data into actionable insights.

Behavioral AnalyticsInteranaThought Leadership
Retailers: Improving Customer Engagement Across Digital Platforms

by Maverick Garner11-06-2018

We all love our digital devices, and as they proliferate throughout our homes, autos, offices, and even clothing, retailers have to figure out how to help customers engage, buy efficiently, and remain loyal. From mobile, to the cars we drive, to the digital wearables we fashion, to our smart homes and cities, we are engaging constantly with our favorite brands, games, content, and people in more and more complex ways.

InteranaThought Leadership
Know How Your Customers Act, Interact, and Transact

by Kelly Brieger04-06-2018

We live in an experience economy – never before has there been such opportunity to turn valuable data into dollars. With a deeper understanding of specific customer actions and interactions, leading brands can make better decisions and revenue-driving updates, faster.

InteranaThought Leadership

The post Know How Your Customers Act, Interact, and Transact appeared first on Interana.

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As of today, businesses have 129 days and counting until Black Friday, which takes place on November 23rd. This is a make-or-break date for many retailers, particularly online entities, who will be counting on the revenue from this massive day of commerce to keep the ship afloat as it sails towards the horizons of new yearly sales. Anticipating this event beforehand – as well as many other holiday sales events that happen after – is critical. We’ve seen businesses make the difficult decision to close their doors due to poor Black Friday performance – which, we’ve come to learn, is almost always a result of two things: poor planning, and & a poor understanding of metrics.

At Interana, we’ve come to agree collectively on a few fundamental passions that helped shape our business – the robustness of being able to see 100% of your data to make the most informed decisions possible, the power of asking unlimited and unbounded questions, and the ability to give every employee that power whenever they have questions.

We would love an opportunity to show you and your business how you can start planning now, Christmas in July, by deploying the Interana platform to gear up for Black Friday, and the ever-important subsequent holiday season sales. It’s time to start now.

Interana is a platform of unlimited questions. No PhD required.

Interana, at its core, is a platform designed to help you understand what your customers do at every swipe, click, view, share, and purchase. Using Interana, any employee within your company can ask an infinite amount of questions about your customers journey, and get answers in seconds. With an easy-to-use-and-understand graphical interface, our platform doesn’t require data scientists and developers to produce reports that can often take months to deliver – every employee can utilize Interana to learn more about specific customer interactions, that suit the needs of their specific business functions.

From product innovation to customer success to engineering, various teams across the company ask specific questions that are vital to their teams’ success. This possibility, especially when it comes to massive promotional sales like Black Friday, lends itself tremendously across the entire company to help determine exactly the types of promotions and product offerings that should be featured – all based on specific questions and historical data. And, teams can know what works and what doesn’t in real time, giving them the ability to make changes on the fly, and also perform A/B testing in various regions throughout the country/world.

To save some time, here are some brief stats to give you a general idea of how businesses have used our platform to make critical decisions:

  • Interana helps users understand what customers do at every click, swipe and view – where are customers clicking? Where’d they come from, and where did they go after their online experience? A near-endless amount of data points can be broken down, analyzed, and used for comparison purposes.
  • Interana can obtain query results from 100% of your data sourced from trillions of customer actions and interactions in seconds.
  • Interana can quickly combine all of your user event data seamlessly to obtain true corrollated results.
  • Interana wants to answer every question you have, and realizes that questions often lead to more questions. So ask an unlimited amount of questions about every aspect of your event data.

November is closer than you think, and Interana is here to help you.

Deploy now and see the results as you promote your business

Let’s put it simply: making the best sales decisions means relying on knowing (not guessing) – if your business considers Black Friday to be a big day for commerce, then it’s time to start thinking about sales and promotions right now. You can take it from us, Black Friday can be a make-or-break holiday sale for many businesses as brands compete for mindshare now more than ever before.

The good news is,129 days is plenty of time to “stand up” your platform of unlimited questions  in time for the big sale – tweaking and altering settings and questions, adjusting parameters and planning for problems, troubleshooting issues that prevent optimal customer experiences, beating the ever-looming, IT “code freeze” – these are all critical considerations that need to be made in advance, before executing to the fullest extent when the big day (or week) finally arrives. But, the time to start is now – waiting until the fall might be too late.

If every retailer knew how to look ahead, well, every retailer would, right? Fact is, consolidating all the necessary data (across all relevant web channels, mind you) is a massive part of getting this done, and is also a tremendously complex undertaking without help from a very robust platform. Interana can help bolster your brand pieces from each disparate data stream covering your entire business – be it via e-mail, customer service calls, social media platforms, in-store purchases, and more. Consolidate your business, across channels, into a single entity, and view all cross-platform data from a single place. Understand what happens across each channel to get a complete view of your customers’ behaviors – every turn, swipe, click, call is documented, helping retailers maximize value for their customers.

You want your customers to shop in a way that is easiest for them, and Interana is designed to consolidate each of these data streams into a simple, easy-to-understand, uniform place for all data. The more you’ve gathered, the more specific questions you can ask to learn even more about your customers’ habits. Forget about pulling data from your Customer Engagement System, combining it with sales data from your online store and the countless other moving parts of the internet that determine your metrics – part of efficiently looking ahead is having all of your data in a single, easy to access place. The ultimate goal? Knowing every action your customers take, at every turn.

Deploying Interana today means you can immediately:

  • Establish and measure customer journeys across an unlimited amount of channels.
  • Test theories, conjectures, and assumptions.
  • Group, compare, and contrast user actions and transactions.
  • Troubleshoot issues.
  • Inspect unexpected data at any time, and for any reason.

Ease of use

Our integrations are measured in days, not weeks or months, and doesn’t require any legwork from your IT or engineering teams. We host our platform in your own virtual private cloud, ensuring that your data is secure –  preventing long cycles with legal and procurement teams. Finally, our very cultural ideals mean we’ve got your back – have questions for us? We’re happy to help you define and understand your metrics, and the platform itself. We’re here to help!

Why wait?

Interana is the only platform that makes it possible for anyone to ask unbounded questions and get answers from all of your raw, disparate, complex data. Interana consolidates that dataset into a frame of event-based reference, so employees can find answers about specific and trending customer interactions across a virtually unlimited timeline, in real-time. Being able to integrate and deploy in mere days means that IT involvement is minimal – with Interana’s managed service, we help deploy, define measurement, and get users started in just a few days.

It’s July, sure, but the holiday season is right around the corner. Be ready.

Learn more and schedule a demo today.

The post Knowing How and When Customers Engage and Interact is Critical to Staying Ahead of the Competition appeared first on Interana.

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Traditional analytical reporting tools simply don’t work. You’re probably employing three or more tools and still can’t get the necessary answers needed to make critical decisions – even after custom coding and queries are deployed to meet the needs of your CEO. Furthermore, business teams across the company have questions, and they expect answers, fast, exactly when they need them. What if you could offer your business teams more than just a single snapshot in time, but an entire movie – a fluid experience – that can be paused (with Blu-ray quality), rewound, rewatched, skipped, and replayed at any point?

For the everyday worker with little technical expertise – but deep knowledge in their domain – Interana offers a flexible way to know more about individual and trending customer experiences in order to make smarter decisions. This shift, especially when it comes to finding forensic information hidden in vast amounts of corporate data, offers a powerful platform that empowers both employees and data scientists to be more successful. Imagine, for a second, the amount of complex, actionable functions  users can achieve with their smartphones – from buying a new home, engaging with a legal expert, or leasing a car, today’s world of digital innovation exists not just behind a screen, but in the palm of our hands. The takeaway? Analytical reporting has always been complicated, and our aim is to make it simple to understand, on any platform, and for virtually any user.

Consider this: Companies who make actionable business decisions based on data will outperform their competition. We stand by this. Interana is built to answer layers of detailed questions, in seconds. We streamline and simplify your complex event data, and consolidate it into one place, ultimately improving workflow and promoting collaboration. Employees indoctrinated with the details of their domain can ask anything about virtually anything – from product development, to customer success, to engineering cycles.

Data Science Synonymous with Product Offering

Interana is fast, provides answers in seconds, requires little build time, and is optimized for up-to-the-minute, event-based data. In a nutshell, this means that employees no longer need to tap the shoulders of data analysts to interpret data, and that whatever inherent data you have can be imported and organized logically, specifically built to answer questions in seconds. Employees can create their own dashboards, manage and interpret customer event data across multiple platforms, and refer to their information and customer know-how metrics without turning to specialists for help.

Data scientists – a critical position in today’s organization – function across such a broad range of departments; and we know from experience that there simply isn’t enough time to help everyone. It’s these very scientists who are quickly realizing the importance of building highly valuable ‘products’ for teams across any given company. When Interana powers the core of these baseline ideals, data scientists are put in a favorable position to empower employees in all departments.

It’s time for companies to deliver innovation to employees – with an easy-to-use interface that simplifies sophisticated analytical procedures to get results, fast. Thousands of employees can now be armed with the means to ask questions and get answers – a new world of corporate-wide engagement – without the need to tap shoulders or bring in additional help.

The benefits from Interana are three-fold:

  1. Unlimited, unbounded questions from 100% of your raw data – current industry tools usually only focus on small percentages of information in order to provide answers in minutes. Interana’s platform doesn’t cut corners, and provides answers based on a company’s entire data landscape, no matter the size or complexity. This allows employees to determine what all of its customers are doing on a virtually unlimited timeline, in real-time, and receive data-driven answers in seconds.
  2. Used by hundreds of employees across the company – Interana was designed to answer questions with simplicity in mind – structured around an easy-to-navigate, interactive user interface. The ability to continue asking questions is what drives more investigation, and more specific answers. The person who thinks of the question should be able to use the platform directly, without having to take requirements to data teams and wait weeks for answers.
  3. Demanding operating environments; initial and continuous ingest disparate data sources – Interana supports hundreds of users per deployment and billions of events per day. The platform ingests massive amounts of data automatically from the cloud (AWS, Azure, Google) and stream (Kafka, Kinesis) in days, and delivers multiple calculations per query utilizing parallel processing, and performs single-pass data scans and linear program executions.

Deploy now: Get the most out of THIS Christmas season

Let’s put it simply: making the best sales decisions means relying on knowing (not guessing). If your business considers Black Friday to be the official kick-off to big holiday promotions, then NOW is the time to start thinking about what brings value to your customers. Black Friday and the entire holiday season can be a make-or-break the entire year for many businesses as brands compete for mindshare and engagement.

129 days is plenty of time to deploy your platform of unlimited questions and get the most out of this coming holiday season.

  • Determine the right dashboards to know in real-time what’s happening
  • Adjust parameters and planning for problems
  • Troubleshoot issues that prevent optimal customer experiences
  • Beat the ever-looming, IT “code freeze”

. . .  these are all critical considerations that need to be made in advance, in order to execute to the fullest extent when the season arrives.

The time to start is now.

The post Are Your Teams Making Decisions Based on Intuition or Data? appeared first on Interana.

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The more years that have passed, the more I’ve begun to realize just how much time I spend sitting at a desk, or behind the wheel of my car. So at the start of this year, I decided to do something about it – it was finally time to hit the gym and get in shape.

A book I was reading called “Mini Habits”, by Stephen Guise, supplemented this ambitious decision. One of my favorite passages from the book posited a maxim that motivated me further: the “Stupid Small Step” plan. The idea is ingenious in its simplicity – in order to create new and useful habits, getting started means setting goals that are, well, and require little to no willpower or significant cost. Aspiring to complete a single push-up on a daily basis is an easily attainable goal to hit, right?

The point of this exercise (workout pun) is to iteratively build progress off of a simple, accomplishable foundation – once a person does a push-up, they’re likely to try another one, and another, and another.

In the weeks since I adopted this effective method of thinking, I find myself exercising more and more (I’m doing more than one push-up a day, for sure). Part of what keeps me motivated is that, at the end of the day, the initial goal is still exceedingly simple: one push-up a day, minimum. So if I find myself tired from a long day at work, or too stressed to push myself physically, I find personal solace in the fact that accomplishing the minimum still means I’m adhering to my daily workout parameters.

It’s that dynamic – setting a low cost of failure to gradually increase returns – that influenced the creation of the article in front of you.

The High Cost of Analytics

Let’s apply this concept to data analysis. Analyzing data, ultimately, is done in order to make important business decisions in order to provide better value for customers – what do customers do? When they do it, and why? It’s a fluid, ongoing quest for answers, buried away in what often amounts to miles of historical numbers and figures.

There are significant cost factors to be considered when making decisions based on data points – mainly time, talent, and theories. Let’s go through each of these factors and discuss the complications they present.

The Cost of Time

There are already a handful of tools that can ingest wide ranges of data. This allows scientists to cut data into pieces, analyze it, and answer specific questions. Doing this is time-consuming for several reasons, which we’re going to touch on.

In the interest of full disclosure (and simplicity), here’s the big catch: questions, in relation to data analysis, are often complex, and specific. Answering nuanced questions requires additional calculations – or a subset of calculations – as well as extra network transactions. This takes a lot of extra time.

Another time cost to consider is the size of the data set itself – “big data” sets, for example, often carry the burden of incredibly time-consuming data scans across billions, if not trillions, of separate events. Even if the system architecture powering these scans is built to be scalable, we’ve learned through experience that the query engine itself, regardless of the solution framework, must be optimized to execute quickly and efficiently.

Finally, even if the questions being asked only require simple answers, businesses are still at the mercy of their data scientists to obtain and share the query results. For busy decision makers, this means more waiting.

Our user interface is built to answer questions, in seconds, allowing virtually anyone to know immediately how customers and visitors act and interact with your brand in a visually intuitive, and easy-to-use manner. No PhD required.

The Cost of Talent

Finding success with any product or service is a matter of visibility. You’ve got to know the needs of customers, existing and new, to determine which aspect of your product provides value to them and their business. This means you’ve got to know every aspect of their day-to-day activities, then determine what processes and interactions your offering can improve.

Though that may sound like a simple endeavor, knowing every user action and interaction in real time and throughout time is an incredibly daunting task. New interactions are created every microsecond, which could add up to trillions of actions per day. Without the ability to ask questions about user activity throughout the day, as part of your everyday job, it becomes impossible to forensically, and specifically, know what kinds of things your customers find valuable, daily and over time, for a vast majority of users.

Sure, an armchair data analyst could write simple scripts to parse the data into useful answers, but not everyone has a data analyst on deck who’s ready to execute in a moment’s notice. This means businesses must hire expert analytic consultants who can define complex and defensible results, outcomes, and metrics needed to make data-driven decisions. This leads to higher costs.

Analytics consultants aren’t dime-a-dozen – cultivating skills to complete these tasks requires years of experience in data analytics and advanced mathematics, as well as a great deal of natural analytical tendencies. Paying for this type of talent isn’t cheap, and certainly isn’t the best solution.

The Cost of Testing Theories

Let’s pretend, for a moment, your business has the time and the hired talent needed to arrange and execute on the queries needed to answer all posited questions. There’s yet another problem: what if the theory being tested is wrong to begin with? This happens more often than you’d probably think, and the only way to reach this determination is by completing the data collection process, and reviewing it. If the initial theory isn’t correct, that means starting the process again from scratch, and putting the data through its paces again.

At the end of the day, every employee with an organization – from marketing professionals to data scientists, have a very specific, and often educated opinion about why their respective theories are correct. But having an analytics professional test every theory would take an unreasonable amount of time and resources.

Our platform allows virtually any user to ask unlimited sequences of questions throughout their workday, as an integral part of their job and success.

How it Adds Up

The bottom line? The cost of obtaining answers about your customers and visitors adds up fast. Adversely, the cost of failure is too high given the potential risk, which is ultimately dependent on the technical know-how of the analyst that’s been hired. Nobody wants to spend big money to test theories that could lead nowhere – that’s really the opposite of doing a single push-up a day. It’s more like trying to do 1,000 on your first go – ambitious, sure, but ultimately limited by an unreasonable foundation.

This is a story we’ve heard from clients time and time again, and it’s this collective sentiment that truly illustrates the problem Interana was built to solve.

Interana and the Low Cost of Failure

At Interana, we subscribe to a “low cost of failure” maxim – we want every member of every organization to feel comfortable and confident that our flexible platform can and will provide answers, no matter what. No data analysts or contractors required.

We’re on a mission to prove this is possible. Using our platform, you can jump right into the deep end of Lake Data and start swimming with no fear of drowning. The more you swim in your data pool, the more efficient (and less exhausting) the process becomes.

Thomas Edison once famously said, “I have not failed. I just found 10,000 ways that did not work.” We built our foundation on these wise words. Part of finding the right answer is finding and identifying the wrong ones, fast. Interana allows users to leverage its comparative nature – continue testing and altering theories, margins, and questions in real-time, as you go.

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The Declaration of Analytics Independence

by Maverick Garner22-06-2018

With the Fourth of July holiday just on the horizon, I thought about what our forefathers must have been thinking that led to the decision to declare independence from England. As I imagined what they were experiencing, what they believed, and how those two things were conflicting within their spirits, I started to realize that I, too, was caught up in a similar conflict with regards to the analytics space, specifically analytics.

Thought Leadership
Virtual Gaming World (VGW) Doubles LuckyLand Slots Average Revenue

by Kelly Brieger18-06-2018

VGW, a pioneering online gaming and sweepstakes company, brings the excitement of hitting the jackpot online with LuckyLand Slots. The company has innovated on various digital platforms while incorporating social connections and multiplayer futures throughout its platform. They needed to know more about how customers played, shared, interacted, purchased, and even got frustrated, would be a critical piece of the puzzle as they introduced new features and functionality. Not only would VGW have to be a leader in creating engaging games and social experiences, but they would also need to become experts about their customers. With this drive to deeply understand customer behavior, VGW needed an analytics solution that could convert their raw event data into an intuitive graphical interface, so that everyone in the company could iterate on questions while getting fast answers. Here’s how Interana helped convert VGW’s raw event data into actionable insights.

Behavioral AnalyticsInteranaThought Leadership
Retailers: Improving Customer Engagement Across Digital Platforms

by Maverick Garner11-06-2018

We all love our digital devices, and as they proliferate throughout our homes, autos, offices, and even clothing, retailers have to figure out how to help customers engage, buy efficiently, and remain loyal. From mobile, to the cars we drive, to the digital wearables we fashion, to our smart homes and cities, we are engaging constantly with our favorite brands, games, content, and people in more and more complex ways.

InteranaThought Leadership
Know How Your Customers Act, Interact, and Transact

by Kelly Brieger04-06-2018

We live in an experience economy – never before has there been such opportunity to turn valuable data into dollars. With a deeper understanding of specific customer actions and interactions, leading brands can make better decisions and revenue-driving updates, faster.

InteranaThought Leadership
In Defense of Pie Charts

by Bobby Johnson14-03-2018

In the world of data analysis, there are few things more reviled than the pie chart. Among "serious" data people, it is at best trivial and naive, and at worst downright evil. I do not agree with this. The pie chart is simple, but that is its beauty. It does exactly one thing and it does it well - it shows you how much different parts contribute to a whole. This isn't the only question you ever have about your data, but when it's the question you do have, the pie chart is perfect. That is not evil, it is not naive. It is data visualization doing what it should - taking something large and abstract and saying something simple about it that your brain can easily internalize.

Thought Leadership
Why Every Employee Needs Access to Behavioral Analytics

by Kelly Brieger03-01-2018

Every employee in your organization already knows how to make smart decisions based on behavioral analytics. They choose their Netflix movies using a sophisticated algorithm, they connect with new Facebook friends based on a cohort analysis, and they make Amazon purchases by leveraging a recommendation engine.

Thought Leadership
How the iPhone X is Changing Analytics

by Kelly Brieger20-12-2017

Ten years ago the iPhone changed human behavior forever. Millions of new applications emerged from nowhere, enabling people to communicate in new ways and live smarter. With the iPhone X, the world is about to change once again.

Thought Leadership

The post How the iPhone X is Changing Analytics appeared first on Interana.

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With the Fourth of July holiday just on the horizon, I thought about what our forefathers must have been thinking that led to the decision to declare independence from England. As I imagined what they were experiencing, what they believed, and how those two things were conflicting within their spirits, I started to realize that I, too, was caught up in a similar conflict with regards to the analytics space, specifically user data analytics.

As an employee of Interana, which is shorthand for “Interactive Analytics”, I enjoy the luxury of meeting with many companies responsible for understanding who their own customers are, their customer’s true experience while consuming their product or service, and why it matters that they know the full story in real-time or over any time they choose.

When I talk to them about their pain or problems attempting to gain valuable insight regarding their customer’s actions, interactions, and transactions, they tell me they’re frustrated with the limit of all their existing analytic tools and solutions, the requirements to be smart or trained before they can get use out of them, and how much time and energy it takes to manifest any useful answers. The list goes on and on and I’ve begun to feel their frustration myself.

Therefore, I decided to imagine what would happen if we declared independence for the analytics community? What if we started a new analytics revolution? What if those responsible for user data analytics today were to pull away and separate from their existing tools or solutions and join us?  Would we be willing to fight for our rights to be free…to explore all of our user data any way we wanted at any time without limits or requirements or the need to be smart enough? I think the answer is “yes”, we would.  And with that said, here’s what I believe that declaration of analytics independence might look like:

__________________________________________________________

DECLARATION OF ANALYTICS INDEPENDENCE

Interana believes in better user experiences and customer journeys for everyone, everywhere, and, as a result, has started that world’s first user data analytics revolution and, therefore, makes the following declaration for analytics independence for all.

FIRST AND FOREMOST, We Believe, that everyone has an equal right to:

  • understand their user event data, what it means, and why it matters
  • obtain their specific query results from trillions of user events within seconds
  • receive 100% of their results regardless of the user event data set size
  • blend user event data sets seamlessly to obtain true corrollated results
  • applying intuition creatively to understand all customer journeys and user experiences
  • ask any number of unbounded or unlimited questions of all their user event data

ADDITIONALLY, We Believe, that everyone should be allowed to interrogate, investigate, or inquire all of their user event data at any time WITHOUT REQUIRING any:

  • type of PhD
  • advanced mathematical skills
  • forensics training
  • data science expertise
  • programming or scripting skills
  • understanding of SQL or SPL

FURTHERMORE, We Believe, that all people within any organization operating within any state, country, or continent, regardless of title, role, department, team, or advisory group should be allowed to freely, equally, and fairly uphold and execute queries against their data to:

  • privately or publicly test their own theories, conjectures, assumptions, or hypotheses
  • discover value currently lying hidden or dormant within the existing user activity data
  • group, compare, and contrast all user actions, interactions, and transactions
  • wildly establish, obtain, and achieve customer success across all channels
  • troubleshoot issues that prevent an optimal experience from occurring for all customers
  • willfully and intentionally inspect the unexpected at any time and for any reason

We Believe, these revolutionary truths regarding user event data analytics to be self-evident and are prepared to fight for and defend against any and all traditional – or legacy-based – analytical concepts, processes, tools, techniques, theory-testing, forethought, or retrospective hindsight in order to raise awareness for our purpose, cause, and direction towards the liberation of all national user event data analytics practitioners and, hereby decree and declare independence from all other non-useful or non-helpful user event data analytical or reporting practices, platforms, or processes. This we declare on this day, July fourth of the year two thousand and eighteen.

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Virtual Gaming World (VGW) Doubles LuckyLand Slots Average Revenue

by Kelly Brieger18-06-2018

VGW, a pioneering online gaming and sweepstakes company, brings the excitement of hitting the jackpot online with LuckyLand Slots. The company has innovated on various digital platforms while incorporating social connections and multiplayer futures throughout its platform. They needed to know more about how customers played, shared, interacted, purchased, and even got frustrated, would be a critical piece of the puzzle as they introduced new features and functionality. Not only would VGW have to be a leader in creating engaging games and social experiences, but they would also need to become experts about their customers. With this drive to deeply understand customer behavior, VGW needed an analytics solution that could convert their raw event data into an intuitive graphical interface, so that everyone in the company could iterate on questions while getting fast answers. Here’s how Interana helped convert VGW’s raw event data into actionable insights.

Behavioral AnalyticsInteranaThought Leadership
Retailers: Improving Customer Engagement Across Digital Platforms

by Maverick Garner11-06-2018

We all love our digital devices, and as they proliferate throughout our homes, autos, offices, and even clothing, retailers have to figure out how to help customers engage, buy efficiently, and remain loyal. From mobile, to the cars we drive, to the digital wearables we fashion, to our smart homes and cities, we are engaging constantly with our favorite brands, games, content, and people in more and more complex ways.

InteranaThought Leadership
Know How Your Customers Act, Interact, and Transact

by Kelly Brieger04-06-2018

We live in an experience economy – never before has there been such opportunity to turn valuable data into dollars. With a deeper understanding of specific customer actions and interactions, leading brands can make better decisions and revenue-driving updates, faster.

InteranaThought Leadership
In Defense of Pie Charts

by Bobby Johnson14-03-2018

In the world of data analysis, there are few things more reviled than the pie chart. Among "serious" data people, it is at best trivial and naive, and at worst downright evil. I do not agree with this. The pie chart is simple, but that is its beauty. It does exactly one thing and it does it well - it shows you how much different parts contribute to a whole. This isn't the only question you ever have about your data, but when it's the question you do have, the pie chart is perfect. That is not evil, it is not naive. It is data visualization doing what it should - taking something large and abstract and saying something simple about it that your brain can easily internalize.

Thought Leadership
Why Every Employee Needs Access to Behavioral Analytics

by Aditya Vempaty03-01-2018

Every employee in your organization already knows how to make smart decisions based on behavioral analytics. They choose their Netflix movies using a sophisticated algorithm, they connect with new Facebook friends based on a cohort analysis, and they make Amazon purchases by leveraging a recommendation engine.

Thought Leadership
How the iPhone X is Changing Analytics

by Aditya Vempaty20-12-2017

Ten years ago the iPhone changed human behavior forever. Millions of new applications emerged from nowhere, enabling people to communicate in new ways and live smarter. With the iPhone X, the world is about to change once again.

Thought Leadership
Top Analytical Skills Every Product Manager Needs in 2018

by Aditya Vempaty13-12-2017

Product managers are modern-day Renaissance women and men. To be successful, PM's must have a solid understanding of the various disciplines in order to inspire and lead a team of disparate skill sets and personality types through the turmoil of product development to a victorious launch.

Thought Leadership

The post Top Analytical Skills Every Product Manager Needs in 2018 appeared first on Interana.

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What happens in Vegas doesn’t have to stay in Vegas.

VGW, a pioneering online gaming and sweepstakes company, brings the excitement of hitting the jackpot online with LuckyLand Slots. The company has innovated on various digital platforms while incorporating social connections and multiplayer futures throughout its platform. They needed to know more about how customers played, shared, interacted, purchased, and even got frustrated, would be a critical piece of the puzzle as they introduced new features and functionality. Not only would VGW have to be a leader in creating engaging games and social experiences, but they would also need to become experts about their customers. With this drive to deeply understand customer behavior, VGW needed an analytics solution that could convert their raw event data into an intuitive graphical interface, so that everyone in the company could iterate on questions while getting fast answers. Here’s how Interana helped convert VGW’s raw event data into actionable insights.

Know what customers are doing. Faster.

Derek Brinkman, General Manager, VGW US, joined the company to help build and maintain its social gaming platform. “At first, in order to know more about critical metrics like cohorted daily retention rates, average revenue per user, and conversion rate, we needed a dedicated member of our engineering team to help us with analytics,” he said. “It worked at first.” Whenever someone on the team needed data to make a decision, they’d spec up the report and give it to engineering. In a few days, they’d get the report they requested. But, we realized fairly quickly that this approach didn’t scale.

“There was too much delay between asking questions and getting answers,” he said. “It was becoming a drag on our ability to make good decisions.”

To fix that problem, the VGW team built a set of dashboards to help reduce the time to get answers. But, they ran into another roadblock. “The dashboards helped us ask high level questions,” Derek acknowledges, “but whenever you’d start to see something that looks surprising, or off, we’d have to ask someone to write reporting logic to drill down further.”

Asking Unlimited, Unbounded Questions Of Raw Data

Derek and his team needed an easy-to-use platform for the entire team, so that they could ask layered questions of raw data and get answers in minutes, not days. They started evaluating whether to check out platforms on the market or build something themselves. Initially, they considered structuring their own data, ingesting it into Amazon Redshift and connecting it to a BI tool. That wasn’t going to be easy: VGW’s data was stored as a myriad of flat event files, not in any structured database. The ingestion and formatting process would take too much time and expertise.

That’s where Interana came in. With Interana, VGW could analyze any event data, as long as it had a timestamp and an ‘actor’ associated with it.

“One of the things we loved about Interana right away was their ability to ingest our data and provide a graphical interface as if we had structured data,” said Derek.

“Every Core KPI We Tracked Went Up”

With Interana, Derek and his team could finally start understanding what customers did and when they did it on their gaming platform. They could answer specific questions to narrow in on customer journeys and experiences. They quickly learned which games & features were most popular, how many spins it took to get someone invested in a game, and even when customers got frustrated and left the platform. Knowing the important details around how customers interact, engage, and connect became a (literal) game-changer. Understanding the players better was just the beginning.

“Because of Interana, every core KPI we tracked went up,” Derek said. “We’ve increased the conversion rate of free to paid users by 2X, month over month retention of payers by 30%, and reduced the time it took to identify and fix issues from weeks to hours.”

Data Exploration Across VGW

The ability to ask questions of our data directly empowers multiple teams at VGW. Below are just a few of the ways VGW uses Interana:

Product Teams

  • Understand which slot games are most successful
  • Prioritize features based on effectiveness of recent feature releases
  • Verify and adjust the math model to change the overall payouts and expected payouts of the games to maximize player engagement
  • Tracking user cohorts over time to find trends in purchase behavior

Live Operations

  • Optimize event prizing and frequency to ensure players stay engaged during live events, tournaments, and quests
  • Understand players’ betting patterns and optimize game operations for maximum lifetime value

Customer Support Teams

  • Optimize VIP player rewards to extend paying player lifetimes and average revenue per VIP player
  • Investigate whether issues are isolated incidents that affect a small group of users or more widespread
Building a Winning Culture

Gaining insights didn’t just yield quantifiable results. It also increased morale across the team. “Knowing more about how to be successful at work is a big motivator to people. When you make decisions based on data, teams feel better about their projects,” Derek said. “Then, when you measure the impact, you can tell your team, ‘Hey, all that effort you put in actually had this effect. Congrats!’ It’s a great feeling.”

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Who Owns Data At Your Company?

by Archana Madhavan26-09-2017

Analytics and business intelligence technologies are advancing quickly, but the data challenge that most organizations face is not technical one, it’s a lack of access to the right data. While every company believes data is important, not every company has been able to build a data culture that gives access to every employee to help them make data-informed decisions.

Behavioral Analytics
How Behavioral Analytics is Changing Manufacturing, Transportation, and the Home

by Archana Madhavan30-08-2017

Traditionally, data streams in from just a few places. Maybe it's user activity on your website. Maybe it's an internal log of orders. The point is, to get a full picture of your company's data you used to only have to link up a couple of databases. But that's all changing now. Valuable data is being generated not just on the web and mobile but on IoT devices, bots, and more.

Behavioral Analytics
Behavioral Remarketing: Bring The Right Ones Back In

by Archana Madhavan14-06-2017

The long-term vision of big data analytics is not a massive warehouse filled with all the world's data. It's a world where you can use data to continuously set up new experiments, learn from your customers, and iterate through answers to your most pressing questions. One of the most important, pressing questions that entrepreneurs ask is, “What's the best way to get people to convert?”

Behavioral Analytics
The Interactive Analytics That Fuels Tinder’s Marketing Team

by Archana Madhavan24-05-2017

Though marketing is somewhere between an art and a science, analytics can still give you an edge when it comes to understanding your product and your users. When marketers can ask and answer questions about users, product, demographics, etc. they’re empowered to connect with their audience and inspire their users. Having data to back up decisions and give insight as to who is using a product, as well as why and how they’re using it is foundational to building a strong marketing effort for any company.

Behavioral AnalyticsCustomer Stories
Top 5 Reasons Not To Roll Your Own

by Christina Noren17-05-2017

OK you have a crack data engineering team that knows all the open source big data tools inside out and can build anything. Why not roll your own system to deliver data insights to the business about the behavior of customers, users and devices? Won’t that cost less and be more tailored to your business? Well, no.

Behavioral Analytics
How E-Commerce Companies Can Drive Profit with Behavioral Analytics

by Archana Madhavan01-05-2017

To say that e-commerce is beginning to dominate the world of retail would not be an exaggeration. Retail e-commerce sales are expected to surpass 2 trillion according to an eMarketer report, with double-digit growth projected to continue beyond 2020. In the U.S. alone, 8 in 10 Americans make online purchases.

Behavioral AnalyticsThought Leadership
The Top IoT Analytics Use Cases Today

by Aditya Vempaty26-04-2017

The growth of the Internet of Things (IoT) has been astonishing. From our cars to our watches to our factories, more and more things are becoming embedded with technology. We can do more than ever before with the objects around us.

Behavioral AnalyticsThought Leadership

The post The Top IoT Analytics Use Cases Today appeared first on Interana.

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We all love our digital devices, and as they proliferate throughout our homes, autos, offices, and even clothing, retailers have to figure out how to help customers engage, buy efficiently, and remain loyal. From mobile, to the cars we drive, to the digital wearables we fashion, to our smart homes and cities, we are engaging constantly with our favorite brands, games, content, and people in more and more complex ways.

Retailers need to find ways to offer new, different, and valuable services, products and experiences. Leading retailers need to find ways to drive valuable shopping experiences, deliver engagement strategies that help the customer journey, streamline the ease and ability to spend more time and money on a retailer’s app or site, and drive shoppers to physical storefronts.

Along with today’s tremendous and growing retailer pain points to increase revenue, deepen loyalty, create trust, increase conversions, and decrease returns, a critical new pain point is top of mind: increase value to get more mindshare on digital platforms.

So, how can retailers think about and implement truly valuable offerings and services to consumers around the world? They need to Stop Guessing and Start Knowing what customers do, how they act and interact, and how to give them value that keeps them coming back.

Tweet: #Retailers: Improving #Customer Engagement Across #Digital Platforms Understanding Customer Journeys and Sophisticated Experiences: Four Pillars

Creating valuable customer experiences is critical as consumers engage with digital platforms — the first step is knowing what they do when they engage.

Here are four ways in which Retail customers use Interana to understand the customer journey.

Attract

Retail customers use Interana to figure out ways to attract new shoppers to online and mobile stores, and re-generate interest with previous shoppers that may have abandoned their carts along their journey. They know that the lifeblood of the business depends on a steady stream of new users visiting to make purchases.

Engage

They also use Interana to continually experiment to figure out new ways to engage loyal shoppers, interact with them, and keep them “curious-to-click.” They can entice customers to follow specific paths, or tailor their journey options based on what they know about customers’ profile, preferences, and propensity to buy.

Convert

With Interana, Retail customers can focus on converting occasional shoppers into regular paying customers as soon as possible, in order to increase purchase rates and create additional streams of online shopping revenue.

Retain

Interana helps retailers do everything they can to retain regular shoppers for as long as possible. A loyal customer is likely a happy customer, and happy customers will evangelize your brand to friends, which leads to gaining new shoppers — and the cycle starts all over again.

Achieving Goals by Knowing Customer Interactions at Every Turn

When retailers fully understand the customer journey, they can reach their goals faster and keep their shoppers coming back. Let’s look at how retailers use Interana to create engaging customer experiences.

Optimizing Content

One use case we often see within Retail is content optimization to educate shoppers on particular products and provide details about items that customers might like. Nothing fights against attracting new shoppers more than bland, mediocre content. No one will click an ad that is not appealing or does not interest the shopper. Poorly-thought-through content can cause potential shoppers to turn away, and not even shop at all. On the other hand, high-value content placed in front of high-value super-shoppers can exponentially increase profits and revenue — it piques their interest in a particular item, and it can be easily shared on social media channels, giving a boost to a brand or sale.

Innovating Product

Our Retail customers focus heavily on innovating website and mobile app shopping experiences through developing product features. By understanding how potential customers are using their web store or app, they customize and tailor the entire shopping experience to make it easier, faster, more valuable, safer, and more engaging, which is valuable to create loyalty and trust. Sometimes, product teams need the freedom to experiment and test new ideas; they need to understand the shopper and know which features work BEFORE they commit money and resources to build and ship.

Making Customers Successful

Retail customers use Interana to commit to the success of their patrons. Satisfied shoppers come back consistently, place more items in their carts, buy more, and spread the word to others. These customers also strive to inspire their super-shoppers in new ways, since inspiration moves toward higher degrees of loyalty, commitment, and trust.

Reducing Customer Headaches

Retailers use Interana pretty consistently to proactively find issues or problems that shoppers encounter and then resolve them fast in order to minimize negative impact or risk to the overall experience. Engineering and operations teams typically use Interana for performance analytics and troubleshooting. Interana also allows them to shorten release cycles. By getting their latest and most valuable features out to shoppers faster, they not only stay ahead of the competition, but they also please shoppers with new points of value in the shopping experience.

Democratizing Data

Retail customers are using Interana to democratize data, to provide real-time answers to team members, corporate-wide. With fast answers on hand, companies can achieve their goals through data, not gut feeling. They obtain a much higher value of customer attraction, engagement, conversion, and retention because more business professionals are thinking and understanding more about customers journeys and experiences. Therefore, self-service analytics is critical in order to move fast, scale quickly, and truly understand all of their shopper’s actions, interaction, and transactions.

Tweet: With fast answers on hand, companies can achieve their goals through #data, not gut feeling Build and Maintain Loyalty & Trust

Retailers need to create as much loyalty and trust with their customers as possible — it is critical to revenue generation. Nothing beats repeat business from loyal customers who trust you, your brand, and your services.

Create Repeatable Value

Creating repeatable value that customers appreciate and want to return to — keeping them coming back to your store or mobile app again and again — is the magic in the world we live in today. Gone are the days where you can afford to deliver basic online shopping experiences. Instead, you need to continually present shoppers with new and fresh experiences that keep them coming back, which gives you more opportunity to upsell or upgrade.

Increase Revenue

At the end of the day, retailers, and every business, need to make sure shoppers are placing as many items in their cart as possible and then clicking the “BUY” button to gain profits — the more the better, of course.

Reduce Costs and Lower Risks

Reducing risks and lowering costs of operations is always a must. Keeping the lights on, and employees paid, is a necessary part of running any successful business.

Gaining more mindshare, engagement and revenue

In order to offer truly valuable services and products in today’s device-driven world, retailers need to understand the customer journey along every step, from what first attracts customers to what keeps them coming back. With Interana, retailers can Attract, Engage, Convert, and Retain shoppers by committing to the customer experience. Mindshare, engagement, and revenue all stem from knowing the customer journey and increasing value along every step.

If you give value to your customers by crafting engaging experiences, they will return that value by coming back to your business — and the cycle continues.

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Thank you!
Know How Your Customers Act, Interact, and Transact

by Kelly Brieger04-06-2018

We live in an experience economy – never before has there been such opportunity to turn valuable data into dollars. With a deeper understanding of specific customer actions and interactions, leading brands can make better decisions and revenue-driving updates, faster.

InteranaThought Leadership
The Why and the How of Interactive Analytics, Part 2

by Matt Green09-04-2018

In Part 1, I talked about why companies need interactive analytics in order to unlock the full potential of their data. Here, I’ll show you how Interana’s features help users interact with their data.

Interana
The Why and the How of Interactive Analytics

by Matt Green07-03-2018

By Matt Green, Director of Product Management at Interana. Our name says it all: Interana is Interactive Analytics. It reflects a deeply held set of beliefs within our company about how people in today’s most innovative companies want to use data in a way that is fundamentally new.

Interana
How We Built Our No-Jerk Culture

by Aditya Vempaty08-11-2017

Some jerks never ask questions. They don’t ask how your day is going. They don’t ask for your input on a project. They certainly don’t ask you for permission to eat your yogurt in the office fridge that clearly had your name written on the label. These jerks have an obvious deleterious effect on morale.

InteranaThought Leadership
Why I care about preserving computer history

by Bobby Johnson03-10-2017

I am deeply honored and excited to be joining the board of the Computer History Museum. I believe this is an enormously important institution in today's world, and I'll try to explain why.

Interana
Hard Problems We Like

by Lior Abraham08-06-2017

You can’t throw a stone these days without hitting an article about “big data.” There’s endless advice on how you can be more “data-driven” (we prefer “data-informed”); how data can drive you and your business to infinite success; how X or Y analytics product will make your data dreams reality.

InteranaThought Leadership
Interana Friends & Family Program: Introducing a new, exclusive way to experience Interana.

by Christina Noren02-05-2017

If you know about Interana you probably know it’s the interactive behavioral analytics solution that some of the biggest and most innovative digital businesses like Bing, Tinder and Sonos rely on to sustain a data-informed culture. These companies use Interana because it’s the only way to give everyone in their organizations the speed, scale and flexibility to ask any question about the behavior of people or things, and get answers back in seconds – even up to the billions of searches, swipes, and song plays that they deliver every day.

Interana

The post Interana Friends & Family Program: Introducing a new, exclusive way to experience Interana. appeared first on Interana.

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