1) The document discusses performance assessment frameworks for digital marketing campaigns of e-commerce firms. It notes that while more consumer data is available, there is lack of clarity around key performance indicators. 2) It suggests segmenting users by engagement and shopping activity levels rather than just demographics, to better tailor campaigns. Segments with low engagement and shopping should be marketed differently than high engagement/shopping segments. 3) The framework aims to justify performance indicators, measure segment efficiency, build assessment models, implement a prototype using real e-commerce data, evaluate results, and specify future agency use. Data envelopment analysis will be used to provide efficiency scores, targets, and dynamic changes across audience segments and profiles.

1. 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.