Accu­racy is a crit­i­cal fac­tor in a con­tent test­ing and opti­miza­tion pro­gram that is too often over­looked. Get­ting the most accu­rate results from your test­ing means you will have bet­ter infor­ma­tion and a clearer, more con­fi­dent pic­ture of cus­tomer pref­er­ences and behav­ior on which to base busi­ness deci­sions. Safe­guards must be in place to ensure the valid­ity of the data sources, the ana­lyt­ics, and the ana­lyt­ics reports that are used to con­vey the data cap­tured within results. Know­ing these safe­guards are in place gives you the con­fi­dence to make busi­ness and user expe­ri­ence deci­sions in real time based on the trends you are see­ing in campaigns.

Ensur­ing accu­racy in the test­ing of mar­ket­ing con­tent involves build­ing an effec­tive test design based on your goals and met­rics, feed­ing the right data and rules into the tool or engine for desired impact, and hav­ing a depth and breadth of recorded results to fil­ter by in order to deter­mine effec­tive take­aways based on a suf­fi­cient analy­sis of the results.

Too often, test­ing and opti­miza­tion solu­tions take short­cuts such as mak­ing quick, broad assump­tions based on a sim­pli­fied view of the test results, skew­ing the data to achieve the desired results, or merely tak­ing an “aver­age view” of a diverse vis­i­tor base. It is impor­tant to under­stand that your vis­i­tor and cus­tomer base is diverse. Dis­tinct, accu­rate cus­tomer pref­er­ences need to be iden­ti­fied in order to pro­vide the best cus­tomer expe­ri­ence, rather than mak­ing broad assump­tions based on a lim­ited view of the data.

Beyond sim­ply under­stand­ing what types of infor­ma­tion will pro­vide you with the best answers,  the soft­ware you use to design and test your dig­i­tal mar­ket­ing con­tent must have built-in safe­guards to pro­tect and secure the accu­racy of results.

The most basic thing that can affect your abil­ity to cre­ate accu­rate test­ing results is the depth and rich­ness of the data avail­able to you. The per­spec­tive that rich data pro­vides can greatly assist in the for­mu­la­tion of the most effec­tive rules or hypothe­ses to test. Many tools sim­ply use the data des­ig­nated to be cap­tured by the tool itself in par­tic­u­lar loca­tions, or even within sin­gle ses­sions, as the basis for high-level test­ing and tar­get­ing assump­tions. How­ever, this lim­ited data set doesn’t pro­vide a com­pre­hen­sive view of cus­tomer behav­ior and the fac­tors that influ­ence it. This can result in the loss of sig­nif­i­cant data points, such as other cus­tomer inter­ests, whether a return vis­i­tor responds dif­fer­ently to the same set of mate­r­ial, or sim­ply whether the user is an exist­ing customer.

His­tor­i­cal data can be par­tic­u­larly insight­ful. Incor­po­rat­ing his­tor­i­cal ana­lyt­ics data into your test­ing can more clearly iden­tify sig­nif­i­cant pref­er­ences and para­me­ters for a par­tic­u­lar audi­ence, or even a spe­cific indi­vid­ual, over time. Also, iden­ti­fy­ing trends within your tests as they occur over time can pro­vide unique insights into fac­tors that affect how peo­ple react to your con­tent. These fac­tors can include cycli­cal events, such as sea­son­al­ity, or sim­ply how the mar­ket­place changes over time. Cap­tur­ing your data’s time fac­tor allows you to see cor­re­la­tions within the data that you might have oth­er­wise missed.

Other types of data that can help improve accu­racy are third-party data sets and cap­tured ana­lyt­ics from areas where the tests aren’t being imple­mented into your test­ing tool. Third-party data includes infor­ma­tion from data providers who com­pile data from myr­iad sources, such as search engines or other web­sites, that helps to inform you where your vis­i­tors are com­ing from and what types of inter­ests they may have out­side of your com­pany. You can use this data to iden­tify richer sub­seg­ments of your cus­tomer set based on these pref­er­ences that couldn’t be known by just cap­tur­ing data within your test environment.

Not hav­ing these data sets avail­able, or the abil­ity to fil­ter your results by these vari­ables, makes your pro­gram blind to their poten­tial impact or influ­ence on con­ver­sion, and severely lim­its the accu­racy of the lim­ited analy­ses you can conduct.

In my next arti­cle, I’ll look at some of the safe­guards that can be put in place to ensure the accu­racy of your test­ing, and what tech­niques are avail­able to you to improve that accuracy.