Title: Performance assessment of digital marketing campaigns for e-commerce firms

Performance assessment is an essential part of media planning and campaign optimisation in digital marketing. However, more data about consumer behaviour online does not bring more clarity in terms of the choice of key performance indicators (KPI). E-commerce firms which can track consumer interaction with a company from an advertising click to the completed purchase still argue about which metrics better reflect customer value for the company.

Essentially, audience segments in advertising are formed with look-alike technology, segmenting users by their sociodemographic characteristics. However, the concept of segmenting users by similar efficiency scores might change the approach to campaign optimisation and connect it to certain targets. Thus, a segment with a low engagement efficiency and a low shopping activity should be marketed in a different way to a segment with high engagement and shopping activity.

The efficiency of audience segments can be formed with reference to a fact of purchase. If users have not bought anything yet from the e-commerce website they should be assessed using their activities that increase the possibility of future purchases. But if users already have experience of shopping with the company they should be assessed mostly by their shopping behaviour. These two types of users’ behaviour can be further referred to as buyers and non-buyers.

Overall, the major objective of this study is to develop an effective performance assessment framework in digital advertising for e-commerce firms. The research objectives are:

To justify the choice of key performance indicators. To devise the assessment indexes for measuring efficiency. To build performance measurement models for each level of assessment. To implement a performance measurement prototype with the data from a real e-

commerce project. To evaluate the results of the performance assessment prototype. To specify the prospective use of the developed model in a digital marketing

agency.

Data envelopment analysis (DEA) has been chosen as the main methodology for performance assessment in this project due to its flexible structure of efficiency scores, targets, peers and special indexes to catch the dynamic changes of efficiency. The top-down approach of DEA provides a high-level picture of a campaigns’ performance with an opportunity to analyse the efficiency of every campaign on the levels of audience segments and user profiles.

The data for the prototype will be extracted from the Google Analytics profile of one of the largest e-commerce businesses of home appliances and electronics in Russia.