About Lee Jacobson

Lee is a video game and entertainment executive and is currently the CEO of Apmetrix Inc., a global provider of next generation multi channel analytics for video game, mobile, digital media and virtual reality companies. His experience spans over 25 years with some of the most well know companies in gaming including Virgin Entertainment, Midway Games and Atari.

Are You Talking When Your Customers Are Listening?

Are You Talking When Your Customers Are Listening? – September 8th, 2014

By: Lee Jacobson, CEO – Apmetrix

While you may be working an 8-5 job or 8-8 job, if you’re a business owner, the landscape of business has been so altered by the Internet that working 12 hours a day is no guarantee you’re active online when your customers are. Your customers can be anywhere and talking about you at any time. Is your business prepared for that?

The heart of any good business is good relationships with customers. The heart of any good relationship is good communication. Good communication is communication that takes place in the moment. If your significant other asks you a question, they don’t generally want an answer in 24-48 hours. They definitely don’t want to wait a week. They want you to engage with them in that moment, to show that you’re listening and thinking about them.

Customers are the same way. Just because you’re sitting at your desk at 3am your time, doesn’t mean that your customers in Malaysia aren’t active online and tweeting at you. Odds are good that, at least some of the time, your customers at home and abroad are keeping strange hours. Even during those odd hours, they bring the same expectations about customer service that your customers bring during normal hours. Just as critical, they are listening to you or for you when they post.

Six hours later, after you knock back that first espresso, they aren’t listening anymore. They’ve moved on to other things. The window of opportunity is closed and, no matter how well-intentioned your reply may be, you aren’t talking to your customers when they’re listening. While this may not be a crisis, it is a lost opportunity to generate positive customer sentiment about your business and brand.

You can’t personally be online all the time, but software can be online and active 24/7/365. Software doesn’t need to take breaks, sleep, and it never gets grumpy – barring a server catastrophe. You can take advantage of always-on software that automates social media messaging based on user behavior and segmentation to help manage the demands of the always on Internet and global customer base.

Message customization and automation, based on segmentation profiles, lets you address the needs of your business and talk to your customers when they are listening. Of course, there will always be a need for human engagement, such as following up to critical comments or addressing atypical questions. Delivering customized, automated responses when the customer is listening keeps the door open for future, specific communication.

Why Do Analytics 2.0 Matter Anyway? Competitive Advantage

Why Do Analytics 2.0 Matter Anyway? Competitive Advantage – August 20th, 2014

By: Lee Jacobson, CEO – Apmetrix

The transition to analytics 2.0 has been bumpy. While the data was there in vast, almost overpowering, quantity, the tools to do anything with it took a while to catch up. That lag between the existence of the data and the applications to make it readily coherent has undermined the perceived value of analytics 2.0. If you’ve been able to get by with single-stream metrics and old methodologies, why do analytics 2.0 matter?

Competitive advantage is a big reason. Even if the value of analytics 2.0 isn’t immediately apparent to every business, big business has invested millions, if not billions, developing the IT infrastructure to analyze big data. That investment wasn’t done on a whim. Being able to translate all that customer data into actionable information about customer behavior and attitudes lets businesses reach those customers more effectively and efficiently across dozens of touch points.

The competitive advantage of that superior understanding of customers is hard to quantify, other than to call it huge. Understanding when, where and how to approach your customers to interact with them at the most receptive time and in the most conducive place can transform business performance. You can more effectively separate cold, warm and hot markets by time of day, mode of communication and even geography.

If traditional mass media communication is carpet bombing, analytics 2.0 turns your marketing efforts into precision surgery. The best analytics 2.0 doesn’t just sift data better. It delivers that information to you faster: another competitive advantage. After all, if you’re getting talked up by a social media influencer right now, it does you no good to find out about that tomorrow or next week.

Real-time or close to real-time reporting alerts you to when and where you’re being talked about online, but also alerts to the emotive content. Knowing about positive discussion lets you draw attention to the discussion, but also interact in real-time with the people who are discussing you. This helps to solidify the good impression your business or product is making, but also extends the conversation and improves the chances of new, potential customers discovering you.

Whatever bumps in the road that slowed the implementation of analytics 2.0, it is here now. Ignoring it and the data that drives it is to ignore a way to develop a competitive advantage in the global marketplace. Analytics 2.0 isn’t mere a fad. It is fast becoming a business imperative.

Analytics 2.0 – So Many Data Sources

Analytics 2.0 – So Many Data Sources – August 5th, 2014

By: Lee Jacobson, CEO – Apmetrix

With data coming at you from so many places, it can be a challenge to make sense of it all. How do I organize it? What’s the most relevant data or data source? How do I deploy my analytics resources to turn all that data into actionable information? The reality is each additional data source can deepen your insight into your customers, but not if you can’t get it processed fast enough to be meaningful.

Getting all of that data crunched into something you can use calls for a different approach. The ideal solution is to get all of it available from a single dashboard where you can run correlations, see where the majority of your customers are coming from, identify where you’re trending and spot opportunities.

For example, maybe your product is building a small, but loyal, customer base in Australia. If you analyze the data from each source independently, you might miss that growing customer base because your Australian customers come to your product through your website, your social media pages or links from blogs that mention your product, but in small enough numbers from each place not to warrant notice. If you have all that data in a single dashboard, connecting the dots that you’ve got traction in Sydney becomes far easier.

The single dashboard approach has another advantage. Condensing everything to one place it saves you time. Rather than needing to download dozens of excel spreadsheets and boiling all the data down, a time killer if ever there was one, you cut straight to the analysis. You find out what you need to know in a matter of hours, rather than days, letting you move on it faster. If you have a dedicated analytics person on staff, she can focus her attention on translating data into information and not on beating 47 spreadsheets into a workable format.

The value of data for most businesses is that it provides you with a means to get a close-to-real-time sense of what your customers are doing or how they are reacting to your products. The longer it takes to make sense of that data, the less accurate your understanding of current customer response. Embracing a single dashboard approach enables you to speed up that process by focusing on the analytics.

Analytics 2.0 – Engagement with Purpose

Analytics 2.0 – Engagement with Purpose – July 21st, 2014

By: Lee Jacobson, CEO – Apmetrix

Developing and sustaining user engagement, be it on your website or via social media, is a key goal for most businesses. The more your users engage, the more the word spreads about your business, brand or product. Yet, as often as not, attempts to create and sustain user engagement are purposeless. How often have you randomly clicked on a product on Amazon only to have ads for that product, which you were never going to buy, follow you around for weeks or months?

That approach to bolstering user engagement is, at best, scattershot. Sure, a few people may buy the product or revisit a business page through sheer dint of repetition, but most will simply become annoyed. Worse, some will decide never to buy the product or employ your business in the future. That is user engagement, but entirely the wrong kind.

That is automation at its very worst. It attempts to brute force sales from customers, rather than meeting customers at the right place and in the moment when they are most receptive to the message. Take marketing emails, for example. The best time of day to send a marketing email is between 8PM and midnight and the best days to send are on the weekends. Open rates and click through rates are highest during those hours and day. Yet, businesses persist in flooding inboxes with automated marketing emails Monday-Friday, 8AM-5PM, when open and click through rates bottom out.

Facebook, by contrast, sees the highest engagement rates on Thursdays and Friday afternoons. People have mentally checked out from work and are looking for something, anything else to do but work. So they sneak off to Facebook to ride out the last few hours of their workday. What does this tell us?

It tells us that engagement efforts that don’t dovetail with the numbers are engagement efforts without purpose. Creating engagement through automation calls for delivering emails, Facebook status updates, and Tweets when people are receptive to them. Of course, individual businesses may find their engagement rates vary and there is geography to consider. Setting your automated messages to default to local time misses the opportunity to engage users elsewhere in the world.

User engagement is critical to turning your online presence into something that delivers a measurable return on investment. That means you must not only craft relevant messages, but your automation must correspond with customer receptivity. Anything else is to trade engagement with purpose for advertising

Analytics 2.0 – Optimizing for Marketing Success: Multichannel Analytics

Analytics 2.0 – Optimizing for Marketing Success: Multichannel Analytics – July 11th, 2014

By: Lee Jacobson, CEO – Apmetrix

In many ways, your business is not your product or service. Your business is your marketing. Bear with me on this one. Nikola Tesla was, in all probability, the most gifted inventor and engineer of his generation. Yet, for all his extraordinary contributions, such as alternating current, he was overshadowed by the legacy of Thomas Edison. Tesla was an inventor, while Edison spent significant energy on marketing.

While the world is more complex today than in the days of Tesla and Edison, it remains true that having the best or most innovate product doesn’t always mean you’ll achieve success. You need to market and you need to be able to identify and respond to changes in customer sentiment rapidly. Of course, therein lies the challenge, especially for marketing teams inside a business.

There are three main problems facing marketing teams: escalating numbers of data sources; data format; and data control. Each new social media channel and sales outlet means a new data source. The numbers of these seem to multiply on a weekly basis. The ways in which these channels and outlets, not to mention any outsourced data center, formats the data is irregular. Finally, marketers often find that data is not under their control. It belongs to other departments, such as sales, or functionally belongs to a data center.

The appropriate multichannel analytics tool in the hands of your marketing team solves all of these problems. The right software doesn’t wait for your team to gather or manually input the data. It reaches out to the APIs of data sources and imports the data automatically. It comes with a built-in conversion feature that takes the more common formatting methods and converts them into a single file type. By placing this kind of tool into the hands of a marketing team, you do an end-run around the problem of who owns the data. Other departments can still access it, but the marketing team can get it on demand.

Of course, to be truly functional and optimize marketing, the data needs a single-dashboard display that can correlate the data from all sources along key metric identifiers. In essence, the tool needs to be able to overcome eccentricities in how data gets labeled and identify commonalities.

The tool that does this enables your marketing team to understand what marketing approaches work, where they work, and use that information to develop a deliberate, optimized, cross-channel approach. This optimized approach to marketing success positions your business to be Edison, rather than Tesla.

Analytics 2.0 – The Future of Data Is Automation

Analytics 2.0 – The Future of Data Is Automation – July 3rd, 2014

By: Lee Jacobson, CEO – Apmetrix

The history of business and industry could just as easily be called the history of process automation. In the distant past, a specialist performed all of the tasks associated with a process to produce a final product. As urban life became more common and demands grew, this approach could no longer meet demand and human beings made machines to aid them in parts of the process. Eventually, when this too proved unsustainable, we build machines that performed the entire process and required human oversight, rather than direct participation. We automated the processes.

Data and data collection used to be, if not precisely simple, fairly straightforward. There were metrics to evaluate production, shipping and sales. Customer sentiment was gleaned from letters or the occasional op-ed piece. Things have changed.

The last decade or so has seen such a rapid expansion in the sources and kinds of data available to business that it is no longer possible for one person to manage all aspects of collection, collation, and analysis. To take advantage of the extraordinary depth of information available from business data requires business owners to do what history dictates: automate.

The analytics industry has been a little slow to catch up to this historical demand. At first the industry focused on single-stream analysis and then it concentrated on surface-level, multi-channel data. The demand, however, can be met. The appropriate analytics tool can now gather data from dozens of discrete online sources, ranging from Facebook to Google Analytics and even iTunes. Just as important, it can take that data in the many formats these data sources employ and convert the data into easy to use Excel.

Of course, compiling the data and even converting it to a single file type only solves part of the problem. There is still the problem of turning that information into something actionable and doing it fast enough to be meaningful. If your business is taking a pounding from one or two unhappy customers on social media, it doesn’t do any good to find out about it next week.

The solution is an analytics tool that not only facilitates data collection, but provides a single dashboard that lets you pull salient information from the data and respond. Your data gathering and analysis should enable you to act quickly in response to customer behavior. The only way to achieve that, in the face of an ever-expanding number of data sources, is through automation.

Analytics 2.0 – User Engagement: Timing for Success

Analytics 2.0 – User Engagement: Timing for Success – June 24, 2014

By: Lee Jacobson, CEO – Apmetrix

In his play, Julius Caesar, Shakespeare wrote that, “There is a tide in the affairs of men. Which, taken at the flood, leads on to fortune…” Put more simply: timing is everything. This is as true for timing your interactions with customers as it is in all other things. While interacting with your customers at any time works for you, interacting with them at the right time can significantly boost user engagement and ramp up your success.

Take Twitter interactions, for example. Twitter moves so quickly that tweets come and go in the blink of an eye. If one of your customers or potential customers Tweets about your business, it means they’re thinking about you right now. Responding within a few minutes will open up the possibility for a dialogue, a chance to answer questions and potentially lead to a sale. At minimum, it will generate goodwill and demonstrate your interest in what customers think.

Now, let’s say that you don’t become aware of the tweet until the next day. Of course, you reply, but the moment is gone. The customer or would-be customer is no longer thinking about your business. They may or may not reply and your tweet back to them comes completely out of context, which means you lose any interested third-parties who were there to see the original tweet. Timing is everything.

The same is true, to a lesser extent, in all communication channels. Sending emails to your customers, either with sales material or informational content, is always a good plan (assuming they’ve opted-in). Sending them emails at an hour they’re likely to see and open it is even better. The global reach of your business, courtesy of the Internet, means timing all communications is more important than ever. After all, 3 in the afternoon in the US is the middle of the night in Hong Kong.

Since you can’t be online all the time to time your communications, you need an automated solution that tracks social media content and responds to it. Fortunately, multi-channel monitoring applications can streamline and display this information for you from a single dashboard.

A multi-channel application enables you to monitor customer discussions and sentiments about your business, but automate responses to frequently asked questions. More sophisticated applications even enable content delivery at reasonable local times, regardless of whether you’re awake or asleep. By leveraging automated monitoring and timed delivery, you stack the odds in your favor that users will engage with your communication. User engagement drives success.

Analytics 2.0 – Beware the Single-Channel Analytics Trap

Analytics 2.0 – Beware the Single-Channel Analytics Trap – June 19, 2014

By: Lee Jacobson, CEO – Apmetrix

The term “Big Data” is not a euphemism. There are businesses that, when confronted with the amount of data they collect, are stunned into inaction. The abundance of data is so vast that making sense of it at a basic level seems incomprehensible, let alone gleaning anything about customer sentiment from it. In this situation, it’s easy to fall into the single-channel analytics trap.

The single-channel analytics trap is the tendency to focus on the analytics from one source that is, or that you believe is, highly valuable. Maybe it’s the data from your website, or from Google+, but you focus on that to the exclusion of all other channels. In some cases, businesses do this because it’s easier. They understand how to get what they want from that particular data set and they default to it. In other cases, the business has a false bias toward that channel.

The truly problematic part of the single-channel analytics trap isn’t just that the data comes from a single source, though that is problematic, but the tendency to assume the insights you glean from that data source generalizes across all other channels. This is a dangerous way to assess customer sentiment.

Customers tend to self-select into or out of using particular channels. For example, the most active users on a site like Pinterest are, at surface level, those engaged by imagery. If your website is dominated by text, but lacking in imagery, the attitude toward your product by Pinterest users – if they have any attitude about it at all – is likely to be lukewarm at best.

Assuming that the results from single-channel analytics generalize to all customers can skew your entire understanding of customer sentiment. Multi-channel analytics cut through the data clutter to provide you with a balanced view of customer sentiment, not just sentiment in a familiar channel. Understanding how customers respond to your product, as well as the terms in which they discuss it, can allow you to reshape your efforts to better effect.

Of course, data volume still gets in the way. Multi-channel analytics has come a long way and automation has arrived. It’s no longer necessary for you to try to figure out the best way to handle data from dozens of sources. A solid, multi-channel analytics application will pull in the data from those sources, convert it into a friendly format, and even consolidate the data on a single dashboard. This lets you glean insight from all of your sources and better grapple with the customer sentiment.

Analytics 2.0 – The Importance in Delivering Relevant Messaging

Analytics 2.0 – The Importance in Delivering Relevant Messaging – May 28, 2014

By: Lee Jacobson, CEO – Apmetrix

Let’s assume you’ve moved beyond the basic positive/negative categorization of social sentiment analysis and that you’re using analytics 2.0 to segregate data into business-relevant categories. That means that you’ve made a conscious effort to listen actively to what your customers are saying about your business and using it to solve problems and craft future strategy, such as running a new marketing campaign that plays off of a previous, well-received campaign. If you are, give yourself a pat on the back because you’re way ahead of the curve. Even so, you can take all that information you glean from analytics 2.0 and do more than just listen, you can respond.

In a very real way, participation in social media, not to mention signing up for email lists or text message lists, is an invitation by customers to receive push notifications. While push notifications from social media, by text message or in the email can be tricky ground, your analytics can help you craft notifications that are timely and relevant to your customers, based on the textual and emotive content of their posts, but also based on factors such as geolocation.

For example, say you own a small chain of stores that are all running a sale on 4th of July fireworks and your analytics flag some serious negative sentiment. Your analytics reveal that the negative sentiment comes from fireworks being out of stock, but the analytics also reveal — via geolocation data — that the negative sentiment is all centered on just one store location. You can use that information to send push notifications out to your customer base that, for example, you’re aware of the problem and will have stock back in the next day. You can also send push notifications that, even though your one store is out of stock for the moment, your location at such and such street still has plenty of fireworks.

By digging down into the data beyond mere surface level happiness or unhappiness, you can pinpoint exactly what kind of problems your customers are having, where they are having them, and talk to them about those specific issues. This approach tells your customers that you’re are, in fact, listening when they talk on social media. Just as important, it tells them that you want to provide them with quality service at every opportunity.

Of course, push notifications go beyond merely what customers are saying about your business. You can use them to your advantage by monitoring what your competitors’ customers are saying about them, using the same kind of specificity in your messaging. For example, if you run a grocery store and your competitor’s customers are complaining about how that store is out of watermelon, but you’re stocked up, you can send a push notification to that effect. A hashtagged Twitter post could read “#competitorstore on such and such street is out of watermelons, but #mystore has all the watermelons you need! Come to 112 Aston Ave.” That post is immediate, relevant and lets a business potentially capture some of its competitor’s customer base.

Push notifications can be a powerful tool in a business’s arsenal, but only if the notifications speak to things that customer’s care about. Does the notification address or solve a problem? Does it make your customer’s life easier? Does it inform them of something actionable, like when your sale on that hot new gaming system goes live? Analytics 2.0 can provide you with the fodder you need to craft the kinds of push notifications that speak to these issues by mining and organizing social media data into categories relevant for your business.

Analytics 2.0 – The Importance of Measuring Social Sentiment

Analytics 2.0 – The Importance of Measuring Social Sentiment – May 22, 2014

By: Lee Jacobson, CEO – Apmetrix

The arrival of Web 2.0, and the social media groundswell it brought with it, signaled a paradigm shift for shift for businesses of every stripe. Entirely new business models appeared overnight and everyone scrambled to make sense of this brave new world. Analytics was no exception to this scrambling and the default was to treat social media the same way it treated everything else, as a numbers game. Analytics focused on the number of likes, followers, retweets and pins. While these numbers did and still do matter — 2000 organically won followers on Twitter gives you profoundly more reach than 50 followers — they lack the sophistication to glean insight into user behavior. This is where social sentiment and analytics 2.0 come in.

Social sentiment aims refers to how customers are responding to your business, your campaigns and even your customer service. In the early days of analytics 2.0, this translated into a binary positive/negative assessment. While a big step forward from a raw number score, this binary split provides limited value for understanding what drives user behavior. Unless user response was overwhelmingly positive or negative, it was hard for the business to understand what worked for customers and develop an actionable plan to capitalize on a win or repair a mistake.

Fortunately, analytics 2.0 has come a long way since then. Effective analytics for social sentiment today take a multi-pronged approach that measures more than the binary. Algorithms can search for a range of relevant terms and quantify data into categories. For example, analytics can rank attitudes or emotions in social sentiment. Where a binary approach might rank a Twitter post that says, “Not impressed with the food at Joe’s Burgerhut” and another that says “Joe’s Burgerhut is the worst food in history,” as simply and equally negative, analytics 2.0 would red flag the second post as much worse and in need of review. The intensity of social sentiment, both at the granular and general level allows a business to craft specific responses and general strategies.

The real value of analytics 2.0 when it comes to social sentiment is dousing a firestorm before it picks up a head of steam. While massive international companies can frequently weather a social media controversy, smaller businesses may not fare as well. For example, McDonalds recently unveiled a new character that has received almost universal negative response in both traditional media and on social media. Odds are good that this negative attention will have little impact on the corporation’s bottom line. For a local store, though, a burst a negative social sentiment from local users poses a much more serious threat to the survival of the business, as that negative sentiment can permanently tarnish the business with its core customer base.

Catching that sudden uptick in negative social sentiment early gives the business the chance to get ahead of the damage or try to resolve the problem publicly before the negative sentiment becomes entrenched. On the flip side, if there is a sudden uptick in positive sentiment from customers, analytics 2.0 can cross-reference the posts or status updates for commonalities. If most of the posts relate to a specific product, deal, or even a store location, the business can use that information to try to replicate the conditions that spurred the positive sentiment in future campaigns or other locations.

Social sentiment can offer businesses a wellspring of information about how and why customers do what they do. Analytics 2.0 can help to transform that big data that many businesses find overwhelming into useful, actionable information about customers by segregating it into appropriate categories, levels of emotional intensity and even by specific business functions.