Starcom MediaVest Group - Product launch Samsung Galaxy S9|S9+

Category: Best Performance Campaign

Client: Samsung Electronics Romania

Year / Domain / Status: 2018 / Telecom / Winner

Strategy description:

Our strategic approach was to engage with our core personas and to deliver them customised content depending on user journey and on the new features of the device. 1. We defined the user journey The upper funnel, defined as a COLD phase, was limited to users interacted with our campaign for the first time. Mid funnel segment, defined as WARM phase, was represented by users who have interacted with our campaign and landed on the website, but did not manifested any purchase intent (clicked on “where to buy” button). Lower funnel, defined as HOT phase, targeted users who manifested a purchase intent (clicked on “where to buy” button). During campaign longtail, we also targeted users that recently bought the newly launched S9 – the OWNER segment. 2. We plotted the segmentation strategy Besides behavioral data as per the user journey segmentations, we added three other segmentation variables in order to reach a very granular homogenous audience. Based on device ownership, we had different segments/ creatives for owners of Samsung, iPhone, Other Android, unknown. Considering level of loyalty to current brand, we split Samsung owners into Loyalists and the so-called "Fencesitters", users that are "flirting" with the idea of a brand change at next purchase. Finally, in order to exploit receptivity, a need based segmentation layer was added on platforms that contained the needed criteria targeting: those that want all that a top device can do, interested in all features & design (Want it All consumers); those that want a device with advanced technical features (Performance Hunters consumers). 3. We designed the map communication matrix For an increased relevancy, we thoroughy designed the sequence of messages based on each segment profile, with profile defined as most granular level as per segmentation axis set. The message flow was build from an image driven communication in COLD phase, to drive brand desirability, to sales driven CTAs in HOT creatives, to push sales. This matrix served as guideline to digital creative agency. 4. We set the measurement framework KPI’s were set across all stages of user journey, each mirrored by a detailed set of metrics closely monitored for campaign optimisation. We measured against reach, views & visits for the COLD campaigns, on conversions (clicks on the Where to buy button) for the WARM campaigns and traffic to e-retailers website on HOT campaigns.


Media plan design followed the consumer journey, and used mainly platforms that allow for high definition of segments based on level of interest in brand and brand need (mainly precision buy). Upper funnel formats were used for cold phase (video, rich media formats, influencers content as social activation), static standard formats were considered appropriate for the mid funnel warm phase and click driven standards formats used for aggressive remarketing in hot phase. Samsung’s global deal with Adobe allowed us to use the Adobe Audience Manager solution as data management platform to track all relevant traits that served for segment build up & media deployment in selected destinations: - Google Adwords for GDN remarketing and bid enhancement in search - Doubleclick Bid Manager for programmatic buy to complement GDN for specific device inventory in cold phase & enlarge remarketing inventory in warm & hot phase - Facebook Business Manager to leverage the wide set of targeting options to build segments as per segmentation strategy & remarketing with conversion driven formats for mid& lower funnel campaigns Detailed KPI were designed for each phase, with an exhaustive list of metrics monitored for optimisation against agreed KPIs. We had to sets of KPIs to optimize campaigns against volume & pricing. For COLD phase we optimized against number of visits & cost per visit (>5 sec visit, in order to track only relevant traffic), for WARM we optimized against conversion (click on “where to buy” and Cost per conversion). HOT campaigns that were leading to retailers’ website, and could not track inside retailers assets) we optimized against CTR (again, due to lack of data, ideally campaign should have been optimized agains conversions data in retailers’ website, if available). A very complex taxonomy was employed for campaign setup, in order to be able to track ad performance throughout the whole journey – from impression to conversion, linking ad server (all creatives, all channels were tracked with Doubleclick Campaign Manager) to Adobe analytics data. Campaign taxonomy allowed for performance measurement on all segmentation axis, which made possible agile optimisation on all targeting variables and different creative messages.

Case visual: