Blumen Research

Data visualization

Over the past month, as I integrate into a new role and company,  I have not had the amount of time I thought I would to write towards the blog and am now trying to pick up the pace.

Over the next while I will focus on the satisfaction importance model that I wrote about, data discrepancies, data visualizations and various models within customer satisfaction that I want to try to implement or research further.

Below is a fantastic example of infographics from the University of Utah, as pointed out by W5.

Click through and take a look.

Software for business analytics & dashboards

After testing the boundaries with my last post on integrating Twitter within time dependent market research reports I am going to try to take a look at a more traditional topic, Software for Business Analytics & Dashboards.

“Business analytics (BA) refers to the skills, technologies, applications and practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning.” Wikipedia

The area of business analytics and dashboards for business intelligence is fairly new to me and I have been researching two tools to possibly assist in market research visualization from the business analytics sector. My preferred choice of software for customer satisfaction and market research analysis is a combination of Minitab and Excel. The two pieces of software I am currently considering to add to the lineup are Xcelius by SAP and GoodData a start up in the analytics space.

My interest lies in integrating research data with customer relationship management data in an easy to understand format, where users would be able to quickly get an upper level view of the impact of customer satisfaction and recommendation on their bottom line and the ability to drill down into specific demographics. The main idea would be to provide the client with a detailed customer satisfaction and recommendation report and then a tailored made dashboard for presentations, meetings with management and real time monitoring.

Xcelsius: My experience so far has been extremely positive. The software comes prepackaged with dashboard examples for sales, marketing, HR, personal finance and other templates. By opening and playing around with the templates you can see how data is linked to the data file (an excel file) and how to filter and drill down within your data set. The dashboards themselves look professional and you can easily change the appearance with a few clicks. Tabbing features also allow you to pretty much build out a small reporting tool rather than a one screen dashboard.  The most impressive feature in my opinion would have to be the What if? Analysis. Where you can play out various scenarios and view their impact, such as raising the budget for a specific department and viewing the impact on sales revenue.

Export: Adobe PDF, BusinessObjects Enterprise, Crystal Reports Server, Flash, HTML, PowerPoint and Word

GoodData: Store your data in the cloud via Amazon Web Services, report, analyze, share & collaborate around your business data. The main purpose is to drill down with your data and visualize your business data utilizing various charting features.
 
“Good Data takes a different approach, assuming we would not be constrained by the container or the cluster. We made ad hoc analysis as fast and simple as prescriptive BI. That means new queries on new data sets are as easy as repeated queries on predicted data. Smart in-memory query processing and extensive results caching get over the performance hurdles.” Good Data Site

Export: Microsoft Excel, PDF format or embed reports into any site.

While the two platforms overlap, Xcelsius seems to offer more choice with regard to data visualization and analysis while GoodData has an option and focus within collaboration.

Twitter market research case study: Paranormal Activity

While I am not a full fledged ambassador of using Twitter sentiment and analysis as a market research tool I can see the benefit in analyzing the data combined with a time dependent market research study using questionnaires and panels.

Over the weekend the indi film, Paranormal Activity purchased by Paramount Pictures, which shot for a reported $15,000 grossed $7.1 million. The market push first included screenings at 12:00 am slots to build up buzz and fans could vote on a dedicated website to bring the film to their city. Paranormal Activity averaged $44,163 a theater over the past weekend, compared with $11,780 Couples Retreat, the number one movie grossing movie over the weekend.

Using a few Twitter Sentiment and Trending tools we can analyze the response to the movie and if combined with a traditional market research study including the economic potential then Paramount can establish how many theaters the feature film should be shown in along with how much should now be spent on further advertising the film.

Twitter Sentiment

This analysis is based on free tools and only to show the types of reports that can be combined with a time dependent market research analysis. I have also not tested any tools that require payment. In no way do I endorse any of these tools.

Overall there appears to be a slightly more positive tone with regard to the film. The overwhelming number of neutral comments has to do with users talking about seeing the film or just mentioning it as a new release and potential view. 

With regard to the sources Twitrratr provided me with the highest number of number of analyzed tweets where 16.1% were positive mentions and 7.1% negative.

Update: As readers have pointed out Twitrrater does a poor job of analyzing sentiment, such as using scary for negative when the film is a horror film. You have to use these tools with a grain of salt and the purpose is only to show the new reach for market research reports by integrating with Twitter and other online results.

Twitter Trends

For trends I gathered data from the free versions of Trendrr, Trendistic and Palm’s trend tracker. You can clearly view the increased number of Twitter posts coming out as the weekend approaches and after users have finally seen the film. 

• Twitter posts per day up 313.9% from 9/17/09 to 10/12/09, 402 posts to 29, 609
• Sunday at 12:00 am Twitter posts spiked due to those midnight screenings
• The high majority of posts originated from the United States as the film was only released nation wide

Trendrr

Actionable surveys

A great article by John Goodman and Patty David from TARP Worldwide Inc. on why customer satisfaction surveys are not actionable was recently written for Quirks.com. I want to focus on the methods they bring forward to create a more actionable survey and expand on those ideas.

Ask direct questions about what went wrong: Pre-populate your questionnaire with a list of things that could have gone wrong.

This is a strong point and according to the authors it helps in uncovering as many as three times more problems. I assume that it provides a base and starting point for clients or consumers to analyze problems they are currently having, a great starting point.

Integrate survey data with other sources: Placing the research data alongside the contact data along with key data describing what the company has done with the client creates a more relevant analysis.

As more CRM applications open application programming interfaces (API) it is imperative on market research to tie this data with customer satisfaction analysis providing companies with a more in depth analysis compared to standard demographics. Sales forces and Oracle both have methods to integrate data with third party applications.

Suggesting specific actions: Start to come up with suggested solutions for at least the top problems within the report.

Where I thought the authors were going to go with this point is to suggest actions that the client or consumer can take right after the survey is complete. If during the development of the survey a company can already establish what some of the core issues that may arise, it would be worth while providing direct solutions automatically emailed to the client after the completion of the survey based on their responses.

By providing clients with preemptive solutions before the entire analysis is conducted company can show a desire to improve and further develop strong client relationships.

Creating economic correlation to research data: Quantify the cost of taking action or failure to take action.

By placing a dollar amount on the issues that will be located in the Improvement area of the Importance Satisfaction model companies will have a better understanding of the impact in improvement on their bottom line.

For the full article check out Quirks.com (free registration is required).

Derived importance in the Importance Satisfaction Model

In the post covering the value of the importance satisfaction importance model I mentioned three areas that have to be taken into account before drawing results from the model. The notion that respondents will correctly identify importance levels for each product or service attribute will now be up for debate.

From the last post:

It is up for debate if customers can correctly identify importance levels for each attribute. When asked an importance level for several attributes what client would not want to indicate that each one is important. You have my business now focus on everything. While not all clients take this approach it is still a situation that occur. On the flip side of having clients indicate importance levels you can use various regression models to put together derived importance levels.

While it true that each respondent would want each and every issue taken care of in a timely and effective manor, they can also distinguish which ones are extremely important and which ones are important. The fewer questions located on the questionnaire the easier it will be for the respondents to identify important aspects. It would take a bit of testing to establish that number, but anywhere around 10 - 15 questions would be fare to nail importance. Over that number and you might be entering into the derived importance territory.

Derived importance

The first step is carefully designing the actual survey. Survey length even if you are going over the 15 questions should still be taken into account so the respondent does not opt out at a certain point or suffer from survey fatigue which will affect satisfaction and derived importance results.

While deciding on the number of questions to include you can conduct qualitative research with a subset of the total target to refine the list of attributes to be included in the survey. The shorter the survey, the more respondents you are bound to have which increases the likelihood of establishing statistically valid results for within segments, just in case it is still difficult to establish the attributes to importance based on the model.

Calculated derived importance is done by correlating the overall satisfaction rating with the satisfaction level for each attribute or by conducting a multiple linear regression and standardizing the coefficients.

Two new partnerships within the data space

Over the past week there were a couple of quite interesting partnerships between technology and research companies. The first was between Ominiture and comScore, while the second and more interesting partnership from the new age market research standpoint was between Facebook and Nielsen.

Omniture and comScore are going to be working together on a new product that will include data gathered from comScore with analytics from Omniture. The two companies will be able to show the audience size and how users interact with the actual site. The partnership stems from the fact that there can often be discrepancies between comScore data and that from Omniture or Google Analytics due to the data extrapolation methods undertaken by comScore.

In the words of the two companies the partnership will blend the separate methodologies for analyzing audience reach. Web analytics will now be combined with panel based audience measures.

“This relationship between Omniture and comScore will enable organizations to unify their online and panel-based audience measurement information, providing more consistent and more comprehensive standard metrics. With the combined offering, publishers and advertisers will be able to automate data integration and reconciliation, eliminate the need for publishers to implement time consuming multiple data collection methods and reduce the labor-intensive steps needed to deliver unified audience measurement.” comScore Press Release

Facebook and Nielsen are partnering to produce better analytics for how ads perform within the social network. From Facebook’s standpoint the partnership will provide the company with an extra push into advertising with corporate accounts. Client’s of Nielsen who maintain campaigns within Facebook will be able to poll Facebook users who have seen the ads to gain a sense of reach and viral effects. The idea is that Facebok will become a force to reckon with within the display advertising business where consumers have to remember the brands they saw and possibly passed along within the network.

While I do believe Facebook will succeed to a certain degree within the advertising space the company has a chance to innovate on a massive scale within online market research. This partnership could be a stepping stone to a new wave of research where the difference between influencers and passive consumers can be seen and the impact they have on market share can be established to help guide product development and advertising.

Improvement Actions and the Importance Satisfaction Model

In order to raise the value of customer satisfaction where through a customer satisfaction index or in percentage you need to focus on the areas that requires improvement and maintains the areas of excellence. In an ideal situation with unlimited budgets each company would be able to focus entirely on every aspect of their business at each point in time to increase customer satisfaction. Since we never deal with ideal situations it would be worth while to tackle the headaches and maintain high satisfaction levels in areas that your client base is already ecstatic with. To correctly establish business operations to focus improvements you can utilize an importance satisfaction model.

Importance satisfaction models are divided up into four quadrants representing four areas of your business. On the x-axis is the importance level as established by the client base and on the y-axis is the level of satisfaction for each attribute. To divide up the model into the four quadrants, the customer satisfaction median is used as the central point dividing the y-axis while the median of the importance levels is used as the central point dividing the x-axis.

Four quadrants can be defined as follows:

Excellent

Attributes located in this area are ranked high in importance and high in satisfaction. It is the responsible of the company to maintain these levels of satisfaction to keep the client coming back and hopefully refer new a couple of new clients in.

Improvement

The work begins now to get this area improved. This quadrant contains all attributes with high importance but low satisfaction levels which in turn affects total customer satisfaction results and will impede a company’s growth.

Surplus

Clients are highly satisfied with these attributes, but don’t view them as being important. The performance of the company within this area will exceed the client’s expectation and should of course be maintained.

Fix, but don’t fret

These are attributes with low satisfaction and low importance. Companies don’t have to pay to much attention to these attributes as client’s don’t view them as being important, however client’s will also be pleasantly surprised by improvements in this area.
Our four quadrants make up the model and is a useful tool to guide management to make decisions on the business operations to focus effort and resources. During times where cost reductions are required management can turn to the surplus area.

As with most models there are considerations that have to be taken into account. I will outline them here and focus on each one in later posts.

1.  It is up for debate if customers can correctly identify importance levels for each attribute. When asked an importance level for several attributes what client would not want to indicate that each one is important. You have my business now focus on everything. While not all clients take this approach it is still a situation that occur. On the flip side of having clients indicate importance levels you can use various regression models to put together derived importance levels.

2.  Since the survey is conducted using ordinal scales (Very satisfied, Not satisfied etc.) it is also debatable whether you can represent the median for satisfaction or importance results as a definitive number.

An area that I will examine will be utilizing sliding scales within surveys, which may fix this issue.

3.  After the model is complete and the four quadrants are established will it then be wise to focus efforts on attributes with the To Be Improved section with higher importance levels or lower satisfaction levels?

Within the subsequent pots I will focus on these areas within the importance satisfaction model, but at the same time it is ready to be utilized by management.

Track emerging trends using the Palm Trend Tracker

In an interesting new advertising campaign and a bonus to market researchers conducting analysis on web trends, palm in collaboration with Federated Media has produced a twitter Trend Tracker. While not the first tracker to hit the market, the free tool is definitely a helpful addition to the mix.

Currently the tool focuses on a 24 hour time period with the current top 20 trends on the left hand menu and tweets on the topic located under the spectacularly gorgeous time chart. Along with the frequency graph the site also includes a twitter map that shows you where the tweets are coming in from.

The site in its current format is not that interesting, but will definitely be getting interesting once they include 30, 90 and hopefully a selection of your own dates to track trends via twitter.

Here’s hoping it improves for the market research community.

Analyzing your competitor’s recommendation levels

Running customer satisfaction surveys on your current client base while not a completely straightforward task with respect to building out the survey and the analysis is at least straight forward with respect to building out the client database. But after completing your survey and establishing the relevant metrics leading to high recommendation levels and economic growth, every company should come back and consider the recommendation levels of their top competitors.

Within every industry there will be scores of competitors with ranging market share. Understanding the core issues leading to high recommendation levels and underlying reasons leading to lower customer satisfaction and recommendation levels of your top competitors will provide your company with the know how to bite into at least a small portion of their market share and possibly focus on a business operation within your own company that otherwise might have gone unnoticed.

Now the main question is how do we target our competitor’s customers to analyze their satisfaction and recommendation levels?

To gather scores for your top competitors there are essentially two methods.

The easiest approach is for businesses that compete for the consumer’s or client’s “share of wallet”, meaning that the buyer may be using several vendors to purchase their products or service or will purchase one category from you and another from a separate vendor.

In this case you can analyze your current share of wallet of your existing client base and within the same survey ask your clients’ which other vendors they use, using a radio button and how likely it is that they will recommend the vendor to a friend or business contact.

The second option which will apply to most companies is a supplement to your customer satisfaction analysis, a short top competitor analysis. For this case you will want to keep the survey short and sweet as the respondents currently have no vested interest in assisting your company. To gather the required data you need to survey a representative sample of the entire customer base, which you should already know since you target the same customer base. Also, make sure to have an accurate and representative sample based on geographic location.

While targeting the customer base for your market you should have a max of four questions on the questionnaire.

1. Using a radio button style question, ask the respondent who their top three vendors are from a list of about the top ten vendors in the industry.

2. In your opinion who is the top vendor in the market?

3. How likely is it that you would recommend [vendor] to a friend or business contact?

4. What was the reason for providing your recommendation score?

After compiling all your responses and ensuring results are statistically significant you will have a birds eye view of the competitive landscape and the recommendation levels for your top competitors as well as why the respondent provided the score.

Taking a look at the entire customer base is more difficult and time consuming than analyzing your own client customer satisfaction which is why the survey itself should be short enough to gain a quick view and a high response rate.

The New York Times Network

Generally speaking the focus of this blog is on market research and lean business strategies. For this post I want to focus on brainstorming ways to save the New York Times. Various posts have been written by well respected individuals and blogs on the issues facing the Times, their insurmountable dept and methods to generate enough revenue to keep the business running in a changing media environment. I hope to expand and hopefully bring light to a new direction for the age old paper.

The guiding premise is that the news paper industry won’t survive as their model is broken. Increasing internet usage, the rise of blogs overlapping with the industry’s focus, mircoblogging and the insistence that content should be free have all assisted in the rapid deterioration of quality though out and researched reporting and analysis. The majority of posts are a few paragraphs and very few cover more than one angle (myself included), there just isn’t enough time. We think, we post, we twitter. Who will be responsible for in depth reporting in a world where time matters for traffic? Who will provide us with the in depth articulate analysis and discussion on various industries from venture capital to tech to business and marketing. I believe the Times should focus on an integrated network on sites and bloggers, The New York Times Network.

If AOL thinks are about to become the main source for content of the new age media, they have another thing coming to them.

What I suggest is as follows:

1. Build out a network of blogs through partnerships with industry experts first and foremost and influential blogs, as is currently being done with VentureBeat, ReadWriteWeb and GigaOM, as a secondary source of information.

Rather than syndicating each post, a select number of posts will be used that will have to be a specified length, thoroughly researched and in accordance with the standards of the Times.

Influential bloggers in their respected fields would be key to the network. Each blogger would have a few of his many posts located within the network and the Times would provide a link back to the blogger. The new network would then be able to focus on niche areas without spending more on journalists and the bloggers would gain more exposure by being a part of the network and hopefully more business.

2. Continue to focus on digital deals like the one with the Amazon Kindle. New deals need to be reached so the Times can become the default new homepage for Firefox, the new Apple Touch, CrunchPad and the Blackberry Storm. If Google can get search partnerships, I see no reason why the Times can’t cut a deal to get a new button located on the various digital platforms taking the user directly to the Times home page.

3. Time to get lean and cut the fat. New ideas to reshape the business model are great, but they need to focus on cutting costs. If Microsoft can go lean and generate great products (Windows 7, Bing …), then the Times can make it happen.

4. Build out a kick ass ad sales team. Go after the big media spenders and stop wasting your time with ad sense.

Each of these points has to be expanded, but it is starting point and base to turn around a company that should thrive as the paper industry folds.