This is small amount of data and is very manageable using the tools engines provide today or a vendor-developed application. Now let's combine those data points with data from click-through and ROI information on inbound searches. Perhaps it's still manageable, but it's easily reaching millions of yearly data points. Using engine-provided or vendor-purchased applications to analyze this amount of data is about as far as most marketers go today to understand and achieve success in their search marketing campaigns. Tomorrow, that may not be enough.
Search budgets are rising along with average keyword cost. More companies are entering search, meaning there are less keyword inventories to bid on, and new opportunities to use search are constantly being offered by the engines. To make rapid, intelligent choices on the where, when, and how of their search dollar spending, marketers are going to need even more data than they typically use now, plus the tools, personnel, and training to make use of it.
Techniques used by offline direct marketers are now making their way into search. Predictive analysis, scenario planning, geo-location, and behavior targeting are all in early stages and companies are looking to make them a part of their search marketing mix. As search marketing moves rapidly forward and becomes more important in a company's overall marketing plan, the need to combine collected information with other company data from past marketing campaigns and/or prior sales results will grow.
These new data sources and data integration opportunities, applied to our 100 word example, could easily equate to hundreds of millions of data points per year -- totally unmanageable by today's engine tools or any current vendor search management application. Enter Business Intelligence tools or BI.
Business Intelligence was a term first used by Gartner in the mid-1990's, then popularized by analyst Howard Dresner. It describes the process of turning data into information and then into knowledge. The intelligence is claimed to be more useful each step along the way.
BI software applications were developed to manage this process, initially utilized by financial and manufacturing operations at larger companies. These companies had complex, rapidly changing data needs, with necessary integration from multiple sources, making it difficult to develop or utilize a fixed application to manage it all -- exactly the problem search is going to have.
BI solved this data problem by providing a flexible technology solution that allowed for the collection and storage of disparate data, then rapidly translating it into meaningful and actionable information that helped the companies manage effectively without guesswork. BI turned chaos and complexity into profit by bringing all of the scattered data points of the business process into focus. This same solution will be extremely suitable for search marketing in the near future.
Some companies already offering BI applications include Cognos, Business Objects, Micro Strategy, and Microsoft. All provide the capability to gather, process, and disseminate decision-making information to a company's business leaders. These applications allow users to practice adaptive data management, making them capable of a flexible analysis of changing market conditions and competitive challenges. These same analytic capabilities could easily be applied to search.
But this requires companies to think outside the box. Besides a BI application, they will need a trained and competent in-house staff or a consultant that both understands search marketing and is extremely proficient in the use of BI analytic tools. Doing so will allow them to gain competitive advantage, make the best use of their search marketing dollars, and see opportunities within search.
The search industry is in its adolescence. As it grows, the task of making it work well for a company will become much more complex. Businesses need to look to the future now and prepare for tomorrow.