Purpose – At present no frameworks exist for services marketers to incorporate social media (SM) within marketing communications planning. The majority of integrated marketing communications (IMC) frameworks were developed prior to the development of the widespread use of digital and SM for information seeking, sales and service. The purpose of this paper is to investigate this issue for services marketers specifically as they differ from FMCG, industrial and durable marketers in terms of marketing messages, branding, media and channels. Furthermore, as they are less reliant on outsourced sale channels they have more potential than other industries to integrate social and digital media to build awareness, brands and sales. Design/methodology/approach – Depth interviews were conducted with eight senior services marketing executives to identify the impact of SM on marketing communications planning, implementation and measurement. Findings – The findings revealed that the unique characteristics of SM (such as interactivity and individualisation, integration of communication and distribution channels, immediacy and information collection) impact traditional marketing communications frameworks. These impacts manifested in 12 modifications specific to services and SM to traditional generic IMC frameworks encompassed by the themes of reach, service channel, word-of-mouth advocacy, consumer generated messages, listening and behavioural measurement. Practical implications – The rapidly evolving nature of SM means senior services marketers need to educate organisational stakeholders regarding implementation issues, which may be a barrier to effective integration of SM within marketing communications. Originality/value – With digital marketing communications budgets reaching 30 per cent within some organisations, it is timely to put forward a marketing communication decision-making framework that first incorporates SM and second is suitable for services marketers.

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The Dirichlet model is an empirical generalization describing and predicting repeated choice amongst a set of competitive alternatives. With the advent of big data, there are many new potential applications for this model. Its developers emphasized one goodness-of-fit statistic, and subsequent researchers have used this along with others. There is, however, no consensus in the literature regarding which measures to use or, more importantly, benchmarks. This paper proposes a suite of six goodness-of-fit statistics developed from the literature to assess the fit of the model and develops two new measures that account for category specific factors enabling the development of benchmarks. It also provides appropriate benchmarks for all statistics derived from 54 FMCG categories in the UK.