Gone are the days when online busi­nesses will throw tech­nol­ogy at busi­ness prob­lems. Don’t get me wrong — technology’s role in busi­ness has never been stronger, but today there’s a dif­fer­ence: the ‘busi­ness’ is rapidly tak­ing over how tech­nol­ogy is used, and is demand­ing tools that are friendly to mar­keters, mer­chan­dis­ers, and other biz types with line-of-business (LOB)/revenue responsibilities.

The other dif­fer­ence is that busi­ness folks are look­ing for tools that help them address spe­cific key per­for­mance indi­ca­tors (KPIs). It’s hard to find new bud­get dol­lars for tech­nol­ogy, but it’s easy to jus­tify invest­ing in, for exam­ple, a tool that will eas­ily auto­mate cross-selling and there­fore increase AOV. There’s no bet­ter exam­ple of this than per­son­al­iza­tion tools such as rec­om­men­da­tions engines. The con­ver­sa­tion we have with cus­tomers regard­ing rec­om­men­da­tions today is about what they’re specif­i­cally try­ing to do at each stage of the con­ver­sion fun­nel, rather than one that sounds like “this year we need to add a rec­om­men­da­tions engine to our site”.

This means that tools that auto­mate the rec­om­men­da­tion of rel­e­vant prod­ucts and con­tent (e.g. help or news arti­cles) must offer a really high level of mar­keter con­trol. From brand look & feel, to how rec­om­men­da­tions are mes­saged, to prac­ti­cal con­sid­er­a­tions like the price thresh­old of rec­om­mended prod­ucts — if mar­keters can’t incor­po­rate their own best prac­tices, the tool is unlikely to accom­plish their spe­cific goals.

Another impor­tant con­sid­er­a­tion: every square inch of online real estate counts. If a mer­chan­diser is going to use some of the that space to show off pop­u­lar arti­cles, sim­i­lar prod­ucts or try to entice an impulse buy at the end of a shop­ping spree, they’d bet­ter be darn sure these rec­om­men­da­tions are per­form­ing. There­fore, it’s essen­tial that busi­ness users are able to eas­ily try out dif­fer­ent rec­om­men­da­tion strate­gies with dif­fer­ent audi­ences, test & com­pare them eas­ily and make changes (and push them live — with­out IT).

As a tes­ta­ment to the grow­ing pop­u­lar­ity of auto­mated rec­om­men­da­tions solu­tions, we’re start­ing to see (over­due) atten­tion to what I call the “new breed” rec­om­men­da­tions prod­ucts by the ana­lyst community.

Susan Aldrich, SVP at the Patri­cia Sey­bold Group, recently eval­u­ated Omni­ture Rec­om­men­da­tions. The report pro­vides a thor­ough review of key areas from her rec­om­men­da­tions eval­u­a­tion frame­work such as rec­om­men­da­tions struc­ture, man­ag­ing rec­om­men­da­tions and inte­gra­tion with other online marketing/merchandising com­po­nents. I encour­age you to down­load your own free copy of this report.

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