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How To Buy Business Intelligence Software | @BigDataExpo [#BigData]

BI buyers need resources that better illuminate what's happening in the market, and how to choose the correct BI software

What Businesses Want From Business Intelligence Software

Business intelligence is a broad topic. Querying and reporting have been BI bread and butter for some time, but other techniques and methodologies have recently come under the BI umbrella: extract, transform, and load (ETL), data federation, real-time analysis - you get the idea.

Similarly, the number of industries beginning to use business intelligence is vast. Healthcare is harnessing predictive analytics to identify and treat high risk patients to reduce hospital admissions across entire patient populations. Automakers are using data from thousands of sensors along the production line to optimize both speed and precision. Zoos are even using geospatial data to uncover which exhibits are most popular with visitors. That's right, even the red lemurs aren't immune to data analytics.

With so much versatility - not to mention so many data analytics companies - it's understandable for businesses to feel a bit of confusion during the buying process. BI buyers need resources that better illuminate what's happening in the market, and how to choose the correct BI software.

To better frame the market for businesses researching BI, TechnologyAdvice gathered and analyzed data from two sources: the product filtering tool on our website, and phone surveys with IT professionals from the past 12 months. The phone surveys were gathered from over 1,000 professionals and our website data includes more than 1,400 requests.

Since the sources aren't equivalent, we didn't combine the data, but rather created a report that contains two surveys. The entire report is pretty detailed, so I will focus on two of our insights into what business are currently looking for.

Insight #1: Forecasting is King, but Social Media isn't Far Behind.

When filtering BI products in the TechnologyAdvice database, 22 percent of users chose sales forecasting as their ultimate goal. Significantly, the ability to make better decisions in the present based on statistical predictions remains appealing for businesses. In truth, forecasting may be one of the main reasons for the popularity of business intelligence. Businesses are obsessed with staying ahead, and what better way than by using data to predict the future?

Forecasting utilizes a number of analytics techniques, such as data mining, predictive modeling, and even data federation. And while it's necessary to emphasize the limitations of forecasting - this technology is fallible and can't make predictions with 100 percent accuracy - the benefits of this particular application remain tremendous.

Social media analysis ranked second behind forecasting. 19 percent of respondents ranked the analysis of unstructured social data as their top priority for business intelligence. The transition from forecasting to social media analytics is an interesting one. Where forecasting involves some of the more veteran elements of BI, social media analytics attempts to harness natural language processing to analyze the emotions of consumers on social media, a process sometimes known as sentiment analysis.

Due to the incredible complexity of the human language, sentiment analysis still lacks perfect precision. 80 percent accuracy is the current benchmark. Advances are being made, but language isn't getting any simpler, so the technology remains far from perfect for the time being. This shouldn't be a surprise, since the depths of context and the subjectivity of meaning in human communication remain difficult for computers to fully grasp.

But, I digress. Businesses want social media analytics so they can complement the "how" of historical, transactional data with the "why" of sentiment analysis to build a more holistic view of their customers. Sure, building a churn model may help prevent customer loss or make upselling more effective, but tying an emotion to each customer interaction can be even more insightful.

Sentiment analysis also helps businesses answer qualitative, rather than just quanititative, questions. While this particular tool is still being refined, the payoff of gaining insight into the "why" of customer actions is valuable enough that businesses are increasingly looking to implement social analysis.

Finally, Logistics and operational analysis rounds out the top 3 most common business goals with 16 percent. The broadest of these three applications, operational analysis can refer to near real-time reporting that's often accessed through dashboards, and that equips users with information they can immediately apply to their workflow.

The practical applications of operational analysis are vast. Customer service representatives form a major user group, because of their need to quickly access entire transaction histories between customers and organizations. However, operational analysis also overlaps with more process-oriented use cases, such as supply chain management or manufacturing, that aggregate and analyze data from a sea of sensors to identify weaknesses in an organization's processes.

The top three most common business goals showcase the eclectic nature of the current business intelligence market. Forecasting helps businesses make better decisions based off of statistical predictions. Social media analytics allow users to comb social media content and pull out conversations about their brand, while operational analysis helps optimize how businesses function.

Insight #2: Most Businesses Are Still Shopping

In addition to inbound lead generation, we also conduct outbound telemarketing campaigns. Over the past 12 months, our outbound team has spoken to over 1,000 IT professionals about business intelligence software, mainly in the context of surveys. Some of the most intersting data for us came from the question "what phase of the implementation process are you in?"

The response was overwhelming: 61 percent of respondents were in the research phase for business intelligence software.

What does this mean if you're in the market for business intelligence? It means take your time. The usability of this software is improving as the demand for analytics across departments broadens the BI user base, and self-service capabilities become common for less technical users.

However, the considerations for warehousing, integration, scale, and usability suggest the purchasing cycle in this vertical is a slow one. And that's fine: given the range of possibilities with this technology, it's paramount to properly vet your options, especially from an SMB viewpoint where IT might not be a strength.

We can extrapolate from this data that BI adoption will maintain its upward trajectory for the foreseeable future. Businesses are certainly paying attention to the competitive advantage data offers them, though the exact method for harnessing such data remains varied.

More Stories By Keith Cawley

Keith Cawley is the media relations manager at TechnologyAdvice. a market leader in business technology recommendations. He covers a variety of business technology topics, including gamification, business intelligence, and healthcare IT.

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