As an Omni­ture con­sul­tant over the past six years, I’ve repeat­edly seen how orga­ni­za­tional issues — not nec­es­sar­ily tech­ni­cal ones — have impeded the suc­cess of many well-meaning com­pa­nies in their quest to become more data-driven. Becom­ing data-driven requires more than just tools or tech­nol­ogy — it requires sup­port­ing processes and peo­ple. Too often com­pa­nies obtain the nec­es­sary tech­nol­ogy, but don’t add suf­fi­cient resources or make changes to their exist­ing inter­nal processes.

Over the past sev­eral months, I’ve cov­ered the “Seven Keys to Cre­at­ing a Data-Driven Orga­ni­za­tion” through a series of blog posts or arti­cles. If you didn’t have a chance to read through the series or view the webi­nar, here are the seven key prin­ci­ples with links to the indi­vid­ual articles:

  1. Secure an Exec­u­tive Sponsor
  2. Align Imple­men­ta­tion with Busi­ness Objectives
  3. Invest in Staffing and Training
  4. Estab­lish and Main­tain Cor­po­rate Standards
  5. Deliver Quick Wins to the Organization
  6. Val­i­date the Data
  7. Hold Peo­ple Accountable

Focus­ing on these seven prin­ci­ples can help posi­tion an orga­ni­za­tion for data-driven suc­cess. Most of the web ana­lyt­ics prac­ti­tion­ers I’ve talked to would say they want to work for a data-driven orga­ni­za­tion … one day. It’s the dream sce­nario for a web ana­lyst. Your analy­sis and rec­om­men­da­tions are impor­tant, trusted, appre­ci­ated, and acted upon.

For most com­pa­nies, the path to becom­ing data-driven is a work in progress. Some of you may be relieved to hear that your com­pany isn’t the only one strug­gling with these prin­ci­ples. It’s true that some orga­ni­za­tions are fur­ther along than oth­ers, and I haven’t yet found a com­pany (espe­cially a large one) that has mas­tered all seven data-driven prin­ci­ples. Sadly, some web ana­lyt­ics pro­fes­sion­als have come to the con­clu­sion that it won’t hap­pen in their life­time at their cur­rent employer and may already be on the job hunt. If your com­pany wants to hire and retain the best web ana­lyt­ics tal­ent, you need to be seri­ous about cre­at­ing and sup­port­ing a data-driven culture.

Data-driven round­table insights

At this year’s Omni­ture Sum­mit, Omni­ture cus­tomers were able to share insights from their com­pa­nies’ data-driven jour­neys dur­ing a roundtable-format ses­sion. Most of the table dis­cus­sions seemed to focus on align­ing the imple­men­ta­tion with the company’s goals through a clear mea­sure­ment strat­egy. Here is a sam­pling of some key take­aways or dis­cus­sion points that the client mod­er­a­tors shared with me:

  • Many com­pa­nies don’t have a clearly defined web mea­sure­ment strat­egy because they have too many cooks (depart­ments) in the kitchen, they focus on soft goals that are dif­fi­cult to mea­sure, they are inde­ci­sive in sep­a­rat­ing what should be mea­sured from all of the things that can be mea­sured, and they don’t appre­ci­ate the full value of what web ana­lyt­ics can do for their orga­ni­za­tion beyond reporting.
  • With­out a clear mea­sure­ment strat­egy, you end up with moun­tains of reports and data which aren’t nec­es­sar­ily help­ful to the business.
  • The best web strate­gies are focused on dri­ving insights and action­able intel­li­gence to improve future per­for­mance, not just a score­card on past performance.
  • The two essen­tial ele­ments in estab­lish­ing a web mea­sure­ment strat­egy are defining/articulating the busi­ness goals and deter­min­ing the KPIs that mea­sure or influ­ence how suc­cess­ful the com­pany is doing in meet­ing those goals.
  • Deter­min­ing the busi­ness goals seems pretty straight­for­ward, but is often dif­fi­cult and con­tentious in prac­tice, espe­cially in larger organizations.
  • When inter­view­ing stake­hold­ers for your mea­sure­ment strat­egy, inter­view at both man­age­ment and indi­vid­ual con­trib­u­tor lev­els. Then cir­cle back with the larger group to intro­duce find­ings, gain buy-in, and plan next steps.
  • Focus on the high­est value KPIs (they’re called “Key” Per­for­mance Indi­ca­tors for a reason).
  • In some cases there is no way of directly mea­sur­ing per­for­mance, so proxy indi­ca­tors need to be used.
  • KPIs should cover not just the top-line results (e.g. sales, leads, etc) but also the key levers or “supporting/contributing met­rics” that impact those top-line KPIs. For exam­ple, if the top-line goal is increased sales, the sup­port­ing met­rics may include things like con­ver­sion rate, aver­age order size, leads, and reten­tion rate.
  • Dif­fer­ent parts of the orga­ni­za­tion may have dif­fer­ent report­ing needs in terms of which KPIs are impor­tant, the level of gran­u­lar­ity required, and the area of the busi­ness they are inter­ested in.

As I men­tioned above, these com­ments were only a sam­pling of the take­aways and key points taken from this round­table ses­sion. The engaged dis­cus­sions at the tables showed how this topic has become top-of-mind for many con­cerned web ana­lyt­ics pro­fes­sion­als and forward-thinking orga­ni­za­tions. It’s great to see how web ana­lyt­ics is matur­ing as a dis­ci­pline at both large and small businesses.

I hope this series of arti­cles has helped you to pin­point key areas where your orga­ni­za­tion can improve in order to become more data-driven. It would be great to hear insights from prac­ti­tion­ers who are expe­ri­enc­ing these orga­ni­za­tional chal­lenges first-hand. I’d love to hear if I’ve missed a key area or prin­ci­ple that has helped or hin­dered your com­pany in its unique jour­ney. As the late Jim Rohn stated, “Labor gives birth to ideas”.