Marketers know what they spend, and their companies know what gets sold. The challenge of marketing measurement is connecting the two. Which customers were touched by which marketing programs? How did those programs affect Web behavior? What nonmarketing factors contributed to the final result? These questions are simple, yet the data often is missing.
The Internet can fill in many of these gaps. Today's marketers can directly measure the Web traffic generated by online and offline campaigns. They can count search queries and blog mentions to see what's on consumers' minds. They can capture attitudes based on message content, measure engagement by willingness to download content and identify influential voices based on their audience. Online surveys can assess consumer reactions to campaigns and make appropriate changes. They can relate individuals' Internet experience to their actual purchases, providing the final link in the chain between marketing efforts and sales results. Taking advantage of this data poses new challenges. The following issues and solutions should be considered.
Changing data sources. Two years ago, few people had heard of Twitter. Today, many companies are obligated to monitor it on a regular basis. The measurement challenge is not simply that new channels keep appearing, but that you may need to begin tracking one literally overnight. Imagine, for example, that you are featured in the next popular YouTube video or mentioned in a prominent social network discussion. Coping with these demands requires very flexible, Web-friendly data integration tools that can adapt to new sources with minimal effort. It also requires analytical databases and reporting tools that can incorporate the new data without major projects to redesign data models, reload old data or rebuild standard queries and reports.
High data volumes. Internet sources can generate massive data streams, particularly when an individual's data is involved. Your reporting system must be able to load and store large volumes, including sudden spikes to many times the size of base levels. You may need automated tools to scan and summarize incoming data and to issue alerts about specified conditions. All this has to happen without degrading performance or losing downtime for database reorganizations.
Ambiguous data. Most Web data is fundamentally anarchic, involving not simply free text, but free text that's misspelled, unpunctuated, in several languages and filled with ever-morphing abbreviations, slang and emoticons. :-( indeed. Now add audio, video, maps, graphics and other formats that are not text-based at all. You'll need powerful data quality tools that can identify unfamiliar elements and resolve them automatically when possible. You also need tools to interpret and classify these contents so you can manage them without paying someone to read every word, listen to every podcast or look at every picture.
New attributes. New media contain new types of data such as social media rankings, connections within a network, paths through a Web site, links to a Web page and numbers of subscribers to a blog. Your systems must capture and interpret this information, monitor changes over time and build it into meaningful reports. This will require sophisticated data parsing, queries, trending and calculations.
Identity resolution. Internet identities have less to do with name and mailing address than network nodes, cookie IDs, user names, biometrics and self-identifying devices such as smart cards, cell phones and electronic license plates. Within legal and ethical privacy limits, you'll want to link these to gain a comprehensive picture of customer media consumption, behaviors and purchases. The sheer variety of potential identifiers will require radical changes to identity resolution techniques. Clever algorithms to find similarities in text strings will no longer suffice.
Mashups. The best way to make sense of Web data may be to view several sources in combination. Many Web products expose their data through application performance interfaces designed to make this possible. Your marketing reporting systems will need to take advantage of these capabilities. In some cases, one of the Web systems may provide a platform to mash together several types of information.
Data exploration. To handle an endless stream of new and shifting data sources, your marketing measurement system must give users tools to explore each source and uncover significant relationships among them. This implies a heavy dose of ad hoc inquiry, data mining and visualization capabilities, all designed for relatively nontechnical users.
Data distribution. Different Web data is relevant to different users. Customer support will be interested in complaints, sales will be interested in product questions and product design will want to see feature requests. Even within marketing, your product managers, promotion managers and others will want different items at different intervals and levels of detail. The marketing measurement system must make it easy for analysts to publish a useful piece of information, for users to share comments on the findings and for users to subscribe to reports they find relevant.
These challenges won't all be met by any one product, but every partial solution fills in a piece of the puzzle. Over time, marketers will gain an ever-clearer picture of how their efforts contribute to business results.
Register or login for access to this item and much more
All Information Management content is archived after seven days.
Community members receive:
- All recent and archived articles
- Conference offers and updates
- A full menu of enewsletter options
- Web seminars, white papers, ebooks
Already have an account? Log In
Don't have an account? Register for Free Unlimited Access