The News Could Be You: Managing Your Brand Reputation Online

By Katlen Tillman | Jun 30, 2010 12:15:27 PM

Online reputation management has become an increasingly hot topic as mass adoption of social media progresses. There are no shortages of issues or drama that overtakes blog posts, trending topics and social commentary, the new reality is that no brand – whether consumer or personal – is exempt. I know I am stating the obvious here, but it’s for this reason that engaging in social media is tenuous for companies and individuals, since there is always a potential for risk; however, whether or not you choose to participate, if something is going to happen it will whether you’re ready or not.

Looking at the new ‘news’ consumer which uses multiple platforms to access the news, with approximately 72% of U.S. news consumers indicating they do so “because they enjoy talking with others about what is happening in the world” (source: Pew, www.pewinternet.org/Reports/2010/Online-News.aspx) suggests that people do so to follow the dramatic narrative that may directly or indirectly touch their lives – and reality can be stranger than fiction.

News isn't just produced in the newsroom anymore.
With the onset of citizen journalism, seemingly innocuous encounters between people in public have the ability to become a 'news' story that is disseminated and shared at a local and global level. The power to elevate an issue is now in the hands of anyone who has something to say. There is happenstance and momentum that can quickly build - catching fire through social channels when fueled properly.

Categories of developing 'news' that have recently inspired conversation waves across the social Web have included:

• Consumer watch groups and commentary on corporate business practices -- such as Nestle and the case with Greenpeace
• Business decisions that can impact consumers -- such as Apple vs. Adobe and the exchanges that ensued once Apple announced that Flash would not be supported on their iPhone and iPad products
• Businesses making decisions or causing situations that impacts society or stakeholders -- such as BP and their focus on traditional media to communicate and then engaging in social media a day late 
• Perception, perspective, or situation related to an individual that spirals out and causes a gossip cycle -- such as Tiger Woods and his long period of silence while social commentary was running amuck on blogs, the Twitterverse, and across Facebook and other social networks.

It can happen to you.
Looking at these scenarios it’s very easy to fall into that place of thinking that ‘it can’t happen to me.’ But you never know when you might find yourself in a situation where a person might misconstrue an interaction and choose to take it online. Brand or personal brand, everyone is at risk at some level.

When managing a company or a personal brand do differences exist?
No way. Both are equally as important in terms of how the crisis is handled, and the same guiding principles are applicable since the damage to reputation can be just as detrimental. A Pew study found that 44% of adults online have searched for information on people who they seek services or consult with professionally. (source Pew: http://www.pewinternet.org/Reports/2010/Reputation-Management.aspx?r=1) Brand, personal or not, managing your reputation online matters.

Here are 6 basic steps for reputation management during a crisis:

1. Listen - Whether you implement a full strength monitoring tool or use something as simple as a Google alert, knowing that something has happened is the first step in moving towards a resolution and not missing a critical development that can be more damaging if left unaddressed.
2. Act quickly yet deliberately - The goal is to address the situation with the right reaction, making decisions from a place of emotion rather than logic in these instances can prove destructive to your brand.  How you’ll act or respond naturally will depend on the situation and the impact, but being deliberate instead of rash is the key, and responding quickly shows responsiveness.
3. Assess whether it’s true or false – If it’s true, face it head on in a professional manner and work to find a resolution, demonstrating that you are listening and acknowledging the situation. Many times taking it offline is helpful. If it’s false, contact the individual through Twitter, their blog or e-mail and in a friendly manner request that the information is corrected. But the main thing here is to be   professional and take the high road, remember that your customers/potential customers are watching.
4. Engage responsibly and with integrity – These are especially important values when engaging online since the repercussions for not being truthful or inappropriate can be long-lasting.
5. Counter pages with pages in search – The more content you put out there, the better you can balance the pages that are in search results. You are definitely in control of the content you create whether it’s on your site, your Twitter or Facebook pages or in forum or board posts.
6. Wash, rinse and repeat, if needed – Some brands are more targeted for attacks than others, and this might be an ongoing process.

Today’s digital world has made aspects of marketing and professional communication more complex than ever. But by starting with monitoring your brand – corporate or personal – it’s that first step towards decreasing risk of not being ready for when a crisis arises.

Machine? Tell me what to do

By Erin Anderson | Jun 23, 2010 5:06:18 PM

Recently I went to get a sandwich and had an experience which my friend and colleague Kat Tillman said- “hey that would be a great blog post.” So, alas this social media strategist is finally walking the walk and posting to the ZAAZ blog. Ok, so here’s the deal – I ordered my sandwich on a super handy kiosk and even paid with the handy-dandy swiper dealy.  Then, decided after a couple minutes of standing in the way of everyone for my completely automated order that I wanted an iced coffee. So I walked over to the adjacent coffee bar (inside the sandwich shop). Did I mention that they give you a vibrating sandwich notifier thingee? Anyway, I waited at the coffee stand for nearly 10 minutes (not exaggerating). Then, Kat (on my behalf) asked one of the 20 plus staff if there was a coffee person around? Their answer back was “did you place the order on the computer?” Hummmmm. No! Why would I think you could order both sandwiches and coffee on their friendly kiosk?  Then it dawned on me ­– technology doesn’t take the place of good customer service. Of the 20 people making sandwiches and managing screens, no one noticed I was waiting to order the old fashioned way. It’s an issue when we spend all our time looking at screens waiting for them to tell us what to do next.  As a gadget girl and social media DB I am here to say – “look up and take notice. There are people (and potential customers) all around you. Are you really engaging with them anymore or are you expecting your technology to take up the slack? Your brand should be enhanced and extended by technology not ruined by it.” I believe no amount of technology, automation or social media can replace good customer service.

Social Media Bill of Rights - Do You feel Covered?

By Jason Carmel | Jun 21, 2010 5:42:23 PM

At last week's 20th annual Computers, Freedom & Privacy (CFP) summit in San Jose, participants and practitioners debated and proposed a Social Network Users' Bill of Rights, designed to represent the denizens of the social ecosystem out there (in here?). Facebook, Google Whatever, Twitter, this is mostly about you guys. You can tell that these principles weren't written by politicians or (exclusively) lawyers, since they are clear, intelligible, and brief enough to be included in their entirety below:

We the users expect social-network sites to provide us the following rights in their Terms of Service, Privacy Policies and implementations of their system:

1. Honesty: Honor your privacy policy and terms of service.
2. Clarity: Make sure that policies, terms of service and settings are easy to find and understand.
3. Freedom of speech: Do not delete or modify my data without a clear policy and justification.
4. Empowerment: Support assistive technologies and universal accessibility.
5. Self-protection: Support privacy-enhancing technologies.
6. Data minimization: Minimize the information I am required to provide and share with others.
7. Control: Let me control my data and don"t facilitate sharing it unless I agree first.
8. Predictability: Obtain my prior consent before significantly changing who can see my data.
9. Data portability: Make it easy for me to obtain a copy of my data.
10. Protection: Treat my data as securely as your own confidential data unless I choose to share it, and notify me if it is compromised.
11. Right to know: Show me how you are using my data and allow me to see who and what has access to it.
12. Right to self-define: Let me create more than one identity and use pseudonyms. Do not link them without my permission.
13. Right to appeal: Allow me to appeal punitive actions.
14. Right to withdraw: Allow me to delete my account and remove my data

Many of these are spot on and so obviously RIGHT, that it makes me a little sad we have to actually tell these business that we expect them. Specifically, Honesty, Freedom of Speech, Predictability, Empowerment, and Protection are complete no-brainers. Clarity is another pet peeve of mine that is well placed on this list- putting your privacy policy in 8 point font and using language indigenous to the British House of Lords circa 1740 is a cheap-ass way of protecting yourself for any skeezy behavior you do after the fact. Any company that fails repeatedly on the above doesn't deserve our attention, let alone our engagement or dollars.

Some principles, thought, are admittedly less clear to me. Data Minimization is an example here, where the intent seems to be something like "Listen, stop asking me for my birth date for a service that doesn't require that data." I get that, and support it. But the flip side is that everyone has a different understanding of what is "necessary," which I kind of also get (does Facebook need your birthday to work? No, but I would guess a lot of people like getting wall posts on their birthdays with well wishes). My take on Data Minimization is that so long as the other principles are adhered to, businesses should feel free to ask anything they want: if their registration form is bloated with irrelevant, overly personal questions, then registrations will suffer as a result. The market will reward the most optimal form with the least friction between click-to-form and registration.

Some principles may actually contradict each other, as well. I look at the Right to self-define as particularly tricky here. If a customer chooses to have 16 unlinked accounts, it arguably puts a significant burden on the business to insure that portability is manageable. If all those accounts are anonymous, does it render the Right to appeal meaningless? (why do I need to appeal a punitive ruling if I can just open up another 16 anonymous accounts)

Still, any critiques of the Bill of Rights are minor, and should be viewed in proper perspective. This is an effective (though certainly not the first) barometer of customer expectations in a digital world where data is aggregated 24/7.

What happens next is always the really interesting question. Will these (or other) principles be legislated? Or will businesses understand which way the wind blows and self-regulate?

What your website says about your brick and mortar sales

By Erik Koto | Jun 3, 2010 4:13:45 PM

 

What can your website activity tell you about your brick and mortar sales?  Ever wondered when your website metrics go up, if it means you’ll actually sell more products offline?  

While ecommerce activity continues to grow in all categories, for many companies the majority of online shopping activity still results in a purchase being made through an offline (brick and mortar) retailer.  As part of our Monetization Modeling practice we analyze this relationship so that we can better understand the role of online actions in the purchase process, and how to optimize the site experience to drive conversion. 

Following is an example of this research, what we learned, and the actions taken as a result.  The products in the example below are high consideration consumer product traditionally sold through a network of retailers (for confidentiality, we’ve anonymized the data).

Methodology and data:

Our research methodologies were correlation analysis and linear regression.  In order for these techniques to be meaningful we needed at least 30 months of both website activity and offline retail sales. For both datasets, we had ‘rolled up’ data (e.g. total site visits, total retail sales) and also product level data (e.g. product ‘A’ web visits, product ‘A’ retail sales). 

HIGH LEVEL SALES ANALYSIS:

With the datasets assembled our first step was analyzing high level relationships.  We ran a series of correlations between online KPIs and offline sales. We started by analyzing site visits, as this represents one of the highest level indicators of consumer interest.  Visits to the website show a fair, but not excellent correlation with offline sales:

Correlation between Website Visits and Offline Sales:  .70

The story becomes more interesting when we begin to look at visits to specific research tools on the site.  In this next graph we are looking at total visits to a group of 5 ‘upper funnel’ product information pages on the site.  These pages contain basic information about the products that a first or second time visitor might rely on to better understand the features of the product.  In this case we see the correlation with offline sales has improved over basic site visits.

Correlation between Upper funnel actions and Offline Sales:  .80

Lastly, we looked at the correlation between a group of 5 ‘lower funnel’ pages and offline sales.  The ‘lower funnel’ pages are actions a website visitor would typically engage in once they are close to the purchase decision, this actions include; finding a retailer, financing options, online inventory search, and requests to be contacted by a sales consultant. The correlation between these actions and offline sales proved to be very strong.

Correlation between Lower funnel actions and Offline Sales:  .90

 

 

High level conclusions and findings:

This analysis immediately yielded insights into shopping behavior.  Clearly, ‘lower funnel’ actions on the web site are a very important part of the purchase process. Their correlation of .90 with offline sales is proof of a very strong relationship between these actions and the purchase decision. 

Another important insight gained from this analysis is the lead time between online research and offline sales.  Prior to this analysis, the client believed users engaged in detailed online research 45 – 60 days prior to product purchase.  In our analysis all three web metrics (visit, upper funnel visits, and lower funnel visits) all show their strongest correlation with same month offline sales. This clearly demonstrated that online research takes place within 30 days of purchase, much closer than previously believed.

PRODUCT SPECIFIC ANALYSIS:

Our next step was to drill down into the data and analyze more specific relationships.  We started by looking the relationship between website actions and offline sales for specific products.  The company had 4 distinct product families.  Within each product family there were 2 to 4 unique products (or SKUs).  We knew from the analysis above that ‘lower funnel’ visits had the best correlations with offline sales, we began by rerunning the same analysis at a product level.  Once again we observed very distinct relationships.

The following table shows the results of product level analysis.  In this case we ran correlation of product specific sales against product specific web activity.  Here we see a distinct difference in correlations between Product Category A, and Product Category B.  Category A shows very strong correlations with offline sales, indicating that online research is particularly important and highly related to the purchase event for these products.  Category B shows the opposite effect, these products show very little relationship between web visits and offline sales.  Indicating these customers are not highly engaged in the web for researching their purchase.

Product Category	Product	Correlation with offline sales
Category A	Product 1	0.79
	Product 2	0.91
	Product 4	0.84
Category B	Product 1	0.40
	Product 2	-0.10
	Product 3	0.52

More specifically, this information can be used to target visitors who have completed specific research activities in Product Category A with timely offers to incent offline purchase.  Since we know these visitors are in market and likely to purchase in the next 30 days, this is a key opportunity to convert sales.

To further illustrate the strength of the correlation between online research and offline sales, we analyzed a single product through a promotional period.  In the chart below, you can clearly see the spike in both online research activity and offline sales during this period.  Knowing the strength of the relationship and the temporal proximity of online research to offline purchase is instrumental in developing timely targeting strategies.

Product specific correlation between Lower funnel actions and Offline Sales:  .91

REGRESSION ANALYSIS:

Our final analysis was to determine which specific online actions were the best predictors of offline sales.  It is important to note, our objective was not to predict product sales on an ongoing basis, but rather understand what actions were the best predictors of actual sales.  Understanding the predictors of offline sales gives us a key insight into the importance and influence of specific online actions.

We built a series of multiple regression models to determine what group of online actions could best forecast actual sales. This was a highly iterative process where we analyzed multiple groups of different KPIs and assessed their R-squared values.  The R-squared metric tells us how well a group of online actions explains the variability of offline sales.  The higher the R-squared, the better that group of online actions are at predicting sales. 

After a series of regression models, we narrowed in on a group of online actions that predicted offline sales with an R-squared of .71 (in this particular application, a very good fit).  Back-testing this model showed a very strong ability to forecast sales based on web site actions.

With the regression model in place and back tested, we had identified a group of 6 online research actions that predict offline sales with a high degree of accuracy.  The completion of these actions signal that a highly qualified visitor is on the site, and should be targeted with specific messaging.  Additionally, since we now had quantitative insight into the most important site actions, modifications to site architecture, on site advertising, and even offsite display advertising, were made to promote these key activities.

ONGOING ANALYSIS

The findings shown above provided the first quantitative insight into the relationship between online actions and offline sales.  These findings provided the rational for changes to content strategy (both onsite and bought media), promotional offerings, and targeting strategies.  The findings also helped to change commonly held notions about how and when consumers interacted with the digital channel. To ensure this was not a “one and done” analysis, we built the capability for easily updated, ongoing correlation analysis into our standard monthly performance reporting.  As the site evolves we can now monitor the correlations between online actions and offline sales, providing us with a new and powerful way to continually optimize the digital channel.