Tech Profile: Loudpixel

What is Loudpixel, and how did you and your team get started in this field?

Loudpixel is a social media research firm. We do social media monitoring, measurement and analysis (consumer insights) for brands and companies. Early in my career, I spent a few years working on the digital teams of large PR agencies doing social media conversation research. We were using Excel to analyze and categorize social media posts to produce reports for companies, and I realized that we could build a better technology around the whole human analysis process to make it more efficient.

We built internal software that lets us import raw data streams from social aggregators and makes it easier for our analysts to add context and sentiment to a sample set of posts, which can then be sorted and built into custom interactive reports within our online dashboard. Rather than trying to automate everything like many companies and tools are trying to do, we’re coming at analysis with a human layer and making it easier for analysts to find deeper meaning and trends in social data.

How should the marketing/advertising industry utilize Loudpixel to create either better end-results or enhance in-house performance?

A lot of companies are paying hundreds or thousands of dollars per year to aggregate social media posts about their companies, and they aren’t getting any real context out of the conversations. Sure, you can look at a tag cloud and get a feeling for some of the keywords that are used a lot, but you’re missing the real context of the conversations, and you’re likely looking at a ton of spam (we find that 5 to 60 percent of social media conversations are driven by spam, so if you’re judging success based on volume alone, you’re probably wasting time and money). We help companies dig deeper to get a real sense for the context of conversations. What percent of conversations are driven by your brand messaging versus organic conversations, for example? What percentage is driven by customer service requests? What are the largest positive and negative conversation drivers, and how can we use this information to make our product or service better?

What trends and changes in the market led you to realize that Loudpixel would fill a void? Describe the void.

There are two sides to social media analysis — theory and execution. In theory, a machine can automatically score all of your social posts, tell you exactly how people feel, who is talking, etc. In reality, automated sentiment is still no better than flipping a coin, data streams are riddled with spam and demographic information usually only covers a small percent of the total conversation. While everyone else is trying to make a smarter machine, we want to educate marketers on how to combine technology and human expertise to get a more accurate, customized report around their brands, companies and industries.

What areas of a business (Customer Service, Research, HR, Marketing, etc.) can benefit most from social media analytics?

We’ve worked with a broad range of business groups, from PR, marketing and brand planning to customer service and product development. From a customer service perspective, more customers are turning to social media outlets to ask for help versus calling up the traditional customer service lines. From a marketing and PR perspective, we’re constantly searching for new opportunities and evaluating sentiment around current initiatives to make changes and drive future programming. From an R&D perspective, we help companies look at industry trends and consumer sentiment around particular products or ingredients. For example, we just wrapped on a report where we looked at consumer perceptions around sugar substitutes. Social perceptions around various substitutes might be one factor that companies take into account when they evaluate the market to create a new product.

How is your team experimenting with how to analyze and display large amounts of data?

We’re always looking at new data sources to analyze. For example, when our clients came to us and told us that they wanted deeper context around what their fans were saying on their Facebook pages, we started pulling the Facebook comment streams into our tool for analysis. We were able to get a deeper level of analysis around how fans were interacting with brands — what types of posts were driving more positive/negative sentiment, what portion of posts were driven by irrelevant or spam content, etc.

How is your team interpreting insights? Why is interpretation of analytics key for clients and agencies?

Social conversation research is becoming another outlet for consumer research on top of more traditional surveys and focus groups. By comparing changes across time or against competitors, it’s easy to see what’s working, what’s not and what actions the company should be taking to make products or programs better.

Allie Siarto co-founded Loudpixel in 2009, along with Jeff Siarto and Ryan Abbott, to create a better way for companies to make sense of social media data. She teaches a class on monitoring and measuring social media for business at Michigan State University. Outside of Loudpixel, you’ll find Allie coordinating Entretrip, a project that brings entrepreneurs together to work abroad under one roof for a week.