Conference planning is starting to ramp up. See our first group of sponsors, and don’t forget the call for papers!
Read MoreThe recent announcement of SAS Visual Analytics highlights four important characteristics of big data that are key to the ability of marketing organizations to use big analytic data effectively:
- Visualization is a challenge for big data analysis and we’ll continue to see new approaches to presenting and interacting with it. Better visualization tools are necessary not just because those who aren’t data scientists need to understand and work with the data, but because the increased efficiency and time-to-reaction to the data is critical in many cases – especially for marketers who need to react with lightening speed to current user experiences.
- In case it isn’t obvious, visualization tools need to work where marketers can access them on web and mobile platforms.
- In-memory data processing is necessary to support the required speed of analysis. This is still rare.
- Big data is not only about unstructured data. Relational data and database tools are still important for incorporating structured data.
SAS is far from the only company driving new big data analytic technology, but they are the biggest and seem determined to stay on the front edge.
Read MoreAjay Agarwal from Bain Capital Ventures predicts that because of the confluence of big data and marketing Marketing is the next big money sector in technology and will lead to several new multi-billion dollar companies. His post is succinct and convincing, but there are additional reasons to believe he is correct.
Marketing spending more on IT than IT
Ajay opens his post with a quote from Gartner Group: “By 2017, a CMO will spend more on IT than the CIO”. It is difficult to judge this prediction without evaluating the supporting research, but it doesn’t sound unreasonable and the trend is unmistakable. Our own experience as conference organizers and consultants offers strong support for the trend. We cover the use of web, mobile, and content technologies for enterprise applications, and our audience has historically been 50% IT and 50% line of business or departmental. Since at least 2008 there has been a pronounced and steady increase in the percentage of marketers in our audience, so that 40% or more of attendees are now either in marketing, or in IT but assigned to marketing projects – this is about double what it was in earlier years. While web content management vendors have moved aggressively to incorporate marketing-focused capabilities and are now broadly positioned as hubs for customer engagement, the real driver is the success of the web. Corporate web sites have become the organizations’ new front door; companies have recognized this; and marketers are demanding tools to manage the visitor experience. Even during the peak of the recession spending on web content management, especially for marketing applications, was strong.
“Cloud” computing and workforce demographics have also beefed up marketers’ mojo. The increased ability to experiment and deploy applications without the administrative overhead and cost of IT or of software licenses has encouraged marketers to learn more about the technology tools they need to perform and helped instill the confidence necessary to take more control over technology purchases. A younger more tech-savvy workforce adds additional assertiveness to marketing (and all) departments. Now if only marketers had more data scientists and statisticians to work with…
Big data and big analytics
Big data has not caused, or contributed very much, to the increase in marketing spending to-date. Certainly there are very large companies spending lots of money on analyzing vast amounts of customer data from multiple sources, but most companies still don’t have enough data to warrant the effort of implementing big data technologies and most technology vendors don’t yet support big data technologies at all, or sufficiently. I agree with Ajay though that the “several multi-billion dollar” marketing technology companies that may emerge will have to have core big data processing and analytic strengths.
And not just because of the volume. One of the main reasons for the enterprise software bias for back office applications was that front office applications beyond simple process automation and contact data collection were just too difficult because they required processing unstructured, or semi-structured, data. Big data technologies don’t address all the challenges of processing unstructured data, but they take us a long way as tools to manage it.
The level of investment in this space is much greater than most realize. Ajay is right to invest in it, but he is not alone.
Read MoreThe call for papers for this year’s conference is now open. See information on the topics and instructions.
Read MoreThe gradual upturn from the worst economic conditions in decades is reason for hope. A growing economy coupled with continued adoption of enterprise software, in spite of the tough economic climate, keep me tuned to what is transpiring in this industry. Rather than being cajoled into believing that “search” has become commodity software, which it hasn’t, I want to comment on the wisdom of Jill Dyché and her Anti-predictions for 2011 in a recent Information Management Blog. There are important lessons here for enterprise search professionals, whether you have already implemented or plan to soon.
Taking her points out of order, I offer a bit of commentary on those that have a direct relationship to enterprise search. Based on past experience, Ms. Dyché predicts some negative outcomes but with a clear challenge for readers to prove her wrong. As noted, enterprise search offers some solutions to meet the challenges:
- No one will be willing to shine a bright light on the fact that the data on their enterprise data warehouse isn’t integrated. It isn’t just the data warehouse that lacks integration among assets, but among all applications housing critical structured and unstructured content. This does not have to be the case. Several state-of-the-art enterprise search products that are not tied to a specific platform or suite of products do a fine job of federating indexing of disparate content repositories. In a matter of weeks or few months, a search solution can be deployed to crawl, index and search multiple sources of content. Furthermore, newer search applications are being offered for pre-purchase testing for out-of-the-box suitability in pilot or proof-of-concept (POC) projects. Organizations that are serious about integrating content silos have no excuse for not taking advantage of easier to deploy search products.
- Even if they are presented with proof of value, management will be reluctant to invest in data governance. Combat this entrenched bias with a strategy to overcome lack of governance; a cost cutting argument is unlikely to change minds. However, risk is an argument that will resonate, particularly when bolstered with examples. Include instances when customers were lost due to poor performance or failure to deliver adequate support services, sales were lost because answers to qualifying questions could not be answered or were not timely, legal or contract issues could not be defended due to inaccessibility of critical supporting documents, or when maintenance revenue was lost due to incomplete, inaccurate or late renewal information getting out to clients. One simple example is the consequences of not sustaining a concordance of customer name, contact, and address changes. The inability of content repositories to talk to each other or aggregate related information in a search because a Customer labeled as Marion University at one address is the same as the Customer labeled University of Marion at another address will be embarrassing in communications and, even worse, costly. Governance of processes like naming conventions and standardized labeling enhances the value and performance of every enterprise system including search.
- Executives won’t approve new master data management or business intelligence funding without an ROI analysis. This ties in with the first item because many enterprise search applications include excellent tools for performing business intelligence, analytics, and advanced functions to track and evaluate content resource use. The latter is an excellent way to understand who is searching, for what types of data, and the language used to search. These supporting functions are being built into applications for enterprise search and do not add additional cost to product licenses or implementation. Look for enterprise search applications that are delivered with tools that can be employed on an ad hoc basis by any business manager.
- Developers won’t track their time in any meaningful way. This is probably true because many managers are poorly equipped to evaluate what goes into software development. However, in this era of adoption of open source, particularly for enterprise search, organizations that commit to using Lucene or Solr (open source search) must be clear on the cost of building these tools into functioning systems for their specialized purposes. Whether development will be done internally or by a third party, it is essential to place strong boundaries around each project and deployment, with specifications that stage development, milestones and change orders. “Free” open source software is not free or even cost effective when an open meter for “time and materials” exists.
- Companies that don’t characteristically invest in IT infrastructure won’t change any time soon. So, the silo-ed projects will beget more silo-ed data…Because the adoption rate for new content management applications is so high, and the ease for deploying them encourages replication like rabbits, it is probably futile to try to staunch their proliferation. This is an important area for governance to be employed, to detect redundancy, perform analytics across silos, and call attention to obvious waste and duplication of content and effort. Newer search applications that can crawl and index a multitude of formats and repositories will easily support efforts to monitor and evaluate what is being discovered in search results. Given a little encouragement to report redundancy and replicated content, every user becomes a governor over waste. Play on the natural inclination for people to complain when they feel overwhelmed by messy search results, by setting up a simple (click a button) reporting mechanism to automatically issue a report or set a flag in a log file when a search reveals a problem.
It is time to stop treating enterprise search like a failed experiment and instead, leverage it to address some long-standing technology elephants roaming around our enterprises.
To follow other search trends for the coming year, you may want to attend a forthcoming webinar, 11 Trends in Enterprise Search for 2011, which I will be moderating on January 25th. These two blogs also have interesting perspectives on what is in store for enterprise applications: CSI Info-Mgmt: Profiling Predictors 2011, by Jim Ericson and The Hottest BPM Trends You Must Embrace In 2011!, by Clay Richardson. Also, some of Ms. Dyché’s commentary aligns nicely with “best practices” offered in this recent beacon, Establishing a Successful Enterprise Search Program: Five Best Practices
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