Following on from Task 1, this blog shall demonstrate different segmentation approaches and target audiences relating to the Mobike app.
|Increase direct traffic to a website
Efficient – shows content to people performing the keyword search
|No insight into why the search is performed
|Locational||Within 1 mile of the product
Specific Wifi Zone
|Measurable to save time – where does CTR work better?||Geo-targeting may lead to locations competing against one another
|Psychographic||Member of a Facebook (FB) group that demonstrates a hobby||Insight into consumers needs/wants
|Requires detailed research|
– Behaviour = keyword search on Google
– Locational = indicated to be in a location via connecting to Wi-Fi
As markets become more fragmented we decided to combine approaches to efficiently target consumers and position the product accordingly. Since our PSO is an app development within a particular city, geographic segmentation plays an important role to specifically target an individual in an efficient area, likewise behavioural is important to find the organisation at their time of need e.g. keyword search.
Risk: These combined approaches have no explanation into a consumer values/needs/lifestyle so the level of market understanding is low.
Discarded: Member of a hobby FB group (psychographic) –data collection process is too time consuming as opposed to secondary data collection methods (p.58), the approach is specific so it reduces/block traffic having a negative effect on the optimisation of the digital offering.
Risk of discarding:
Psychographic targeting establishes an emotional connection to target potential consumers and thus increases the likelihood of acquisition.
Using the combined segmenting approaches, in Table 1 below we have identified several target audiences in which we would use for the MoBike App (our PSO).
|#1||Highly relevant keyword search – increases traffic to MoBike landing page
|Competition for Google rankings
|Competitive rivalry with current integrated journey apps e.g. Uber|
|#3||Captures traffic in response to wider search queries||No MoBike stations near Arndale – no demand for app|
Chosen: TA who search into Google ‘how to get from A to B’ that indicate to be in Manchester via Piccadilly Wi-Fi Zone
– Motivate customers to engage with your brand and its associated products
– Both the search (bike hire) and the landing page (MoBike) is relevant to the user, so hopefully increases C.T.R in hope of an interaction, then later conversion
Risk: A main issue with this choice is that currently MoBike does not show as a transport option on Google, to optimise this would be very expensive and time consuming. If MoBike did integrate their app into this search there would be competition from global company Uber.
Discarded & why:
#1 – Too much competition for the ad-word increases risk to ROI,
– Search term too broad to show city bike hire schemes
#3 – Although relevant to the PSO, it is too broad of a search (mass competition, less visibility, misleading search results)
Risk of discarding:
#1 – Miss out on potentially large market (24.5 million pass though station annually), people often plan their route whilst on their journey to the station.
Lauren Maguire (15073629)
Emma Plenty (15068314)
Yousaf Majid (14044114)
Peter Nelson (15084679)
Alice Harling (15075761)