Pop quiz: One of these charts rep­re­sents the query vol­ume for “back to school” on Google and the other rep­re­sents the num­ber of unique users com­ment­ing on sev­eral brand Fan pages that are actively pro­mot­ing back-to-school mar­ket­ing cam­paigns on Face­book. Can you tell which one is which?

1

2

The answer to the ques­tion is that A rep­re­sents the total num­ber of daily active users on Face­book of back-to-school brands, and B rep­re­sents query vol­ume on Google for terms related to “back to school.” At first glance we could not tell the dif­fer­ence. Both graphs show a sim­i­lar trend: a rel­a­tively sta­ble pat­tern until early July when both show a sharp increase in activ­ity. The only dif­fer­ence is in the mag­ni­tude; B shows a much sharper increase than A.

Social sig­nals vs. Search sig­nals: Same difference?

The currently-held notion is that Search and Social sig­nals are fun­da­men­tally dif­fer­ent. Search is a more direct-intent-based sig­nal that reflects a shop­per late in the sales cycle, while data from Face­book rep­re­sents some­one ear­lier in the fun­nel. How­ever, the above data sug­gests that both sig­nals are very sim­i­lar. So should we treat Search and brand engage­ment sig­nals in the same way?

Yes and no. Yes as the above exam­ple shows that con­sumers’ engage­ment behav­ior on Face­book and intent behav­ior on Google fol­low a very sim­i­lar tem­po­ral pat­tern. No because they fun­da­men­tally rep­re­sent dif­fer­ent behav­ioral aspects. Face­book com­ment data indi­cates how many and how fre­quently users are engag­ing with brands on their Fan pages, while Google query data indi­cates what ques­tions, prod­ucts or ser­vices need imme­di­ate answers. The sim­i­lar­ity in time trends means that both of these behav­iors are tak­ing place simul­ta­ne­ously albeit in dif­fer­ent channels.

Lever­ag­ing the cross-channel effect

The data reveals sev­eral inter­est­ing trends in con­sumer behav­ior. First, while the con­text of con­sumers on Face­book and Google is dif­fer­ent, they are often pur­su­ing a sim­i­lar end goal. In this case, they are look­ing to buy back-to-school related items. Sec­ond, these activ­i­ties are tak­ing place simul­ta­ne­ously. Finally, they are often switch­ing back and forth between the two chan­nels before mak­ing the final pur­chas­ing decision.

Adver­tis­ers would do well to con­sider these insights when for­mu­lat­ing their mar­ket­ing cam­paigns. They must engage and actively man­age the per­cep­tion of their brands within the Face­book envi­ron­ments. Simul­ta­ne­ously they must also have a sub­stan­tial pres­ence on the search engines to guide con­sumers dur­ing the intent stage of the sales funnel.

Read­ers of this blog know that there is a sig­nif­i­cant cross-channel effect when it comes to direct mar­ket­ing — between 40–50% of con­ver­sions that begin with a social ad con­vert on a dif­fer­ent chan­nel. The above trends also tell us that there is a sig­nif­i­cant cross-channel effect in the research phase of the pur­chase process (impres­sions are the early stage met­ric in paid Search while com­ments on brand fan pages are the Face­book ana­log). Adver­tis­ers must also have a cross-channel track­ing and opti­miza­tion solu­tion in place to under­stand the nature of their traf­fic and answer the hard ques­tions, such as what is the effect of the posts they (the adver­tis­ers) make on the paid Search, organic and direct web­site traffic.

Thus, as CMOs look to max­i­mize the ROI of their social media efforts, they must revisit all their assump­tions. They must plan their mar­ket­ing cam­paigns holis­ti­cally con­sid­er­ing all the cross-channel effects. A siloed view of chan­nel per­for­mance would only give a nar­row under­stand­ing of con­sumer behav­ior and could lead to deci­sions that would leave money on the table.

Dr Sid­dharth Shah
Sr. Direc­tor, Busi­ness Analytics

I would like to thank Sara Miller, Busi­ness Ana­lyst at Con­text Optional, for help­ing me com­pile the data.