Posts Tagged ‘Big Data’


Facebook Exec Mike Buckley on How PR Pros Can Use Data

Thursday, October 23rd, 2014
Facebook Mike Buckely Data PR BurrellesLuce Media Measurement Press Clipping Media Monitoring

by flickr user r2hox under CC BY-SA

by Kristan Nicholson

Besides being a devoted husband, father of two girls and member of the 40-something-man band “The Love Handles,” Mike Buckley is also VP of Global Business Communications at Facebook.

On the final day of the PRSA 2014 International Conference in Washington, D.C., he tells the crowd of more than 800 communicators that “Facebook’s mission is to give people the power to share, to make the world more open and connected. The ONLY way we can do this, to service our 1.3 billion customers, is through the use of data, math and analytics.” And every PR person in the room cringed. “Gasp!  Math?!”

He asked how many people in the room majored in math, data or analytics in college and maybe one person responded. But we all measure results, right? This proves that we can use data without math; we just need to embrace it and not be afraid of it. We can become analytical without being a math expert, as simple analytics can have tangible benefits and drive business results. We must correlate our press results with business metrics. Test small audiences, look at K factor (the virality of a story), review social chatter (small clusters of people who are responsible for majority of chatter), and communicate with that group.

Buckley continued to tell us that data equals power; data equals intelligence; data keeps executives from panicking.  And there are three laws of news cycles: Understand the cycle; shorten (or extend?) the cycle; and get ahead of it.  None of us can manage what we can’t measure. None of us can advise what we don’t measure.  And if we (PR pros) don’t do it, how can we ever get a seat at the table?

Every other executive function does their jobs grounded in data and analysis, and we need to pick up our game. Several ways we can do this is by having lunch with someone in our company responsible for analytics. Marry PR with their art. Push our clients to spend money on analytics. Fight for the right to test.  And most importantly: approach everything with an ethical framework. Always do the right thing.

Mike concluded with a story, which seemingly challenged everything he’d just told us. He started by saying: “The biggest lever on Facebook reputation has to do with the experience people have with their product.” Their best day was the launch of their “Look Back” video. When Jesse Berlin’s dad made a video standing in his living room with tears flowing down his cheeks begging someone at Facebook to help him recover his late son’s “Look Back” video, it didn’t go viral. It didn’t have a K-factor.  And data would never explain John’s pain. Because regardless of the fact that data can tell us so much, predicting business outcomes will never replace human action. And there should be days when data simply shouldn’t matter. Mike’s team retrieved Jesse’s video for his dad and THAT is what it’s all about.

 

 

The Infographic Guide to Measuring Your Public Relations Efforts

Monday, April 7th, 2014

Measurement has been a big topic in PR for decades, but it continues to dominate our discussions because the digital age has given us more tools, metrics, and points to measure than ever before. We know it’s important to establish measurable goals and set benchmarks, but what about the actual tools for measurement? How do we get started with the tons of data at our disposal?

Ensure you’re measuring the correct things – outcomes, not outputs – and consider integrating tools like Balanced Scorecard, the Barcelona Principles, and the Sources and Methods Transparency Table. Learn how to use big data the right way by deciding your most important metrics and making decisions based on facts and evidence.

To help you fill up your public relations measurement toolbox, we’ve created this measurement primer. For more detailed tips and insights, check out our newsletter, Finding Meaning in Measurement.

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How to Personalize a Brand Experience Without Being Creepy

Thursday, March 20th, 2014

How to Personalize a Brand Experience Without Being Creepy Ellis Friedman BurrellesLuce Fresh IdeasBrand personalization has never been more vital to providing a unique brand experience and capturing and maintaining customer loyalty. But with so much data available, it’s also easier to annoy or unnerve customers with over-personalized suggestions or communications. Here’s how to use your available data to provide a personalized user experience without seeming like Big Brother.

Be transparent

Inform your users as to what info you’re capturing, how you will use it, and who can see it.  Unnerving customers with specific, personal information on recommendations or personalized experiences will likely cause them to shy away from a brand instead of embrace it. So be transparent: ask for permission to use their data, and provide an opt-out.

Use data provided directly to your brand

It’s one thing to personalize experience based on data a customer has already provided to your brand, whether it’s a previously stated preference for a room on the lowest floor of your hotel or a purchase history that shows they buy the same product at regular intervals. But it’s another thing to use information they didn’t provide to your organization.

Social media posts that mention your brand directly also generally fall into the realm of usable for personalization, but tread carefully. At Qantas Airlines airport lounges, iPads alert staff members when a lounge guest posts content tagged from that location, even if the user doesn’t mention Qantas by name. Staff can then share certain posts with their own followers.

While those posts are public information, some users found that social listening off-putting, especially since, in the case of Qantas, they weren’t directly interacting with the brand on social media and Qantas does not alert their lounge members that such monitoring is in progress. (See: Be transparent)

Tread carefully with third-party data

Using third-party data from social media sites can quickly veer into “creepy” territory. If your brand wants to access, say, Facebook like information, it’s wise to consider clearly asking for permission. General rule: Unless a client clicks the “like” or “follow” button on your brand’s page, be very clear about your third-party data processes and consider using other personalization means.

Personalize better

In a national loyalty study, Maritz Loyalty Marketing found that while 94 percent of loyalty program members want to receive communications from the programs in which they participate, only 53 percent of those members found those communications personalized and relevant. Allow customers to help with that by providing the opportunity for them to customize their interactions with you, either by creating personalized interaction defaults or how they set up and manage a loyalty account. On The New York Times online, users can view recommendations for articles based on recently-viewed articles, and the site provides data on the sections and they view most, an excellent way for members to not only track their own usage, but also feel that The New York Times is pointing the way toward tailored content.

Be selective with the data you use

Big data has huge personalization potential, but brands must use it responsibly; just because you have access to certain data points about a user doesn’t mean that data should be used. Take for example the OfficeMax mailer addressed to “Mike Seay/Daughter Killed in Car Crash/Or Current Business.” Just as it’s important to know what big data metrics are most applicable to your company, it’s also vital to know which of those data points should be used in personalization.

How do you personalize your brand experience? Where do you think the line is between highly personalized and creepy?

This Week’s Shot of Fresh: Big Data in Da House, reddit Right, and Narcissystem

Friday, February 14th, 2014
flickr user John Revo Puno under CC BY ND 3.0 license

flickr user John Revo Puno under CC BY ND 3.0 license

Shot of Fresh is our (mostly) weekly roundup of the latest Fresh Ideas content.

Is Big Data Better Data?

Big data may be the big buzzword, but unless your organization adjusts its culture to value fact-based decision making and real-time feedback, big data investments could turn into big GIGO investments.

How to reddit: Marketing Through the Anti-Social Feeding Tube of Social Networks

A lot of the web’s viral content gets filtered through reddit, but since it’s not a social network and doesn’t have the intuitive user-friendly interface of one, how can marketers and PR pros use reddit to their advantage? Here’s a primer on how to reddit.

Jargonology Episode 5: Narcissystem

Enough about what we think about our content, what do you think about our content? The latest word to add to the jargon jar is narcissystem, and chances are, you’ve dealt with one.

Is Big Data Better Data?

Monday, February 10th, 2014

Is Big Data Better Data? Ellis Friedman BurrellesLuce Fresh Ideas

What do you think when you hear “Big Data?” If you’re anything like me, you hear some syllables that conjure up an image of lengthy Excel sheets. If you’re more precise, you know that it’s all that data that organizations and computers collect on a daily basis.

But is bigger data better data? There are a lot of factors that determine whether investing in big data will actually help your organization and its efforts.

The biggest issue is that big data can easily turn into GIGO – Garbage In, Garbage Out. You may be pulling in gobs of data every day, but if you don’t know how to use it, don’t get to see it, or don’t know what your most important metrics are, that data is all but useless.  Harvard Business Review has an excellent article (registration required) tracking seven case studies of companies that used their data, how they did it, and whether they used that data effectively or not.

The gist? Using big data – and even small data – effectively takes a lot of preparation, implementation, and adjustment. In many instances, it won’t pay off to jump right into big data if you don’t yet have a grip on your small data. Here are some key takeaways, whether your data is big or small:

Start small

Start by learning to use the data to which you already have access. Most existing CRM or ERM systems obtain a lot of useful data, but many organizations don’t know how to access and/or use it. According to Kapow’s survey, only 23 percent of respondents think their big data initiatives have been a success. So before you go investing in big data, think about what you’d like to do with that big data once you have it. Whether its reforming processes, reorganizing, or restructuring, use the data you already have to start small reformations.

Dedicate resources wisely

Be prepared to dedicate a significant portion of your resources to coaching and training. HBR found that the most important factor in successfully becoming a fact-based decision-making organization was consistent, continuous coaching aimed at improving performance of every individual, especially those who are decision-makers.

Provide real-time feedback

Start providing daily feedback before trying to implement new big data changes. Determine one key metric to focus on (the metric will be different for different departments and different levels) and provide the department with the updated metric every day. HBR found that this not only helped managers determine how to best spend their time, but caused those at lower levels to increase precision and efficiency. Just make sure it’s the right metric; it may take some finessing.

Shift the culture

An organization will not magically change by virtue of investing in big data. HBR found that if the organization had a tradition of fact-based decision making, performed engineering and research functions or was web-native, then it was poised to gain the most from big data.

So don’t just look at the shift to big data as an investment and software issue; instead, organizations need to consider it a major shift in company culture. Like any major culture shifts, it will take a while. Give it time, and allow any revised data processes the leeway to produce flawed data – it will improve, and those involved with the data will, with the proper coaching, seek to improve that data.

According to the Kapow survey, 85 percent of business and IT leaders agree that big data helps make intelligent business decisions and foster a data-driven organization. And for organizations that are data-driven and fact-based decision makers, there is a lot of potential in big data.

Last month I attended the Big Data in Motion Summit, where the speakers were Jack Norris, chief marketing officer for MapR Technologies; Pat Pruchnickyj, product marketing director at Talend; and Clarke Patterson, senior director of product marketing at Cloudera. All speakers expressed enthusiasm for the impact big data can have on organizations. And little wonder – they all work for companies that provide big data solutions.

The conference was intended to educate attendees about big data’s potential, results, and myriad of advantages, though the speakers mostly talked about platform options and advantages of their own services. Patterson pointed out that 64 percent of organizations invested or were planning to invest in big data in 2013, so of course, getting the down-low on services is pretty necessary.

Norris explained that the need for big data is driven by three V’s:

Volume (by 2020 enterprise data volume will be four times higher than it was in 2009)

Variety (data is both structured and unstructured and gathered from a myriad of devices, processes, and sources, and stored in different ways)

Velocity (large organizations produce massive amounts of data. Facebook gathers 100 terabytes per day, WalMart has 1 million transactions per hour)

There are plenty of organizations that stand to gain from big data if it’s implemented wisely, but it’s not the “big” part of data that provides benefits – it’s learning to use data big or small in the correct way. No matter the size of your data, you still need to know your key metrics and how to base decisions around those metrics. The opportunities data provides come down to leveraging the data you have into powerful insights and harnessing it in an efficient, fact-based way.