DIGITAL INTERACTIVE SERVICES
Using marketing analytics to drive superior growth
Marketing analytics have been derived from marketing data for decades. Previously, large marketing analytics firms were sought after by large brands to perform analysis on data obtained over a period through print, radio, and television. The number of marketing channels, modes of consumption and delivery have exploded in the digital age, making it challenging for marketeers to provide accurate insights to companies and consumers.
Marketing analytics was previously largely one-sided with companies using data to improve revenues while focusing on messaging and branding for a large consumer segment, typically a geographical or demographic segment. Analytics were reviewed for product performance over a multi-year period through long-term measurements and broad insights. The digital age marked by superior technology has shifted the focus of marketing analytics to personalised insights and almost real-time measurements.
Significant shifts in marketing analytics were caused by:
- Social Advertising explosion – With each platform having their own sophisticated suite of ad products and targeting capabilities, to connect and engage with customers
- Ubiquity of mobiles – Currently in 2022, nearly 83% of people on earth own mobile phones. These are the consumers’ preferred mode of engagement with any product or service enabling brands to capture behavioural and emotional data.
- Video-centric marketing – With a mobile phone, anyone can create and stream videos to promote products, themselves, influence customers, deliver tutorials and review anything. They are leveraged to improve conversions.
- Digital-first generation – With millennials using digital media as the preferred mode of engagement with anything they do, expecting instant interaction, gratification and customer service is a given. Analytics generated through engaging content, interactive ads and recommendations enable organisations to meet such expectations and are thus key to driving product growth.
- Data is big – With omnichannel decision influence, gathering data through every step of a customer’s journey, drives marketing analytics engines to generate real-time insights enabling businesses to deliver targeted ads, offers and enhanced modes of customer service through artificial intelligence and superior customer service.
Marketing Analytics can be used to drive superior product growth in today’s complex environment through evolving measurement methods that were traditionally used. These are –
- Mixed Media Modelling (MMM) – A method that enables marketing teams to measure the impact of marketing campaigns, their influence and performance. MMM provides insights into trends like seasonality, brand equity and holiday effects over a long period. MMM is limited to non-granular data, does not consider relationships between channels, has very limited insights into brand messaging and does not factor in customer experience.
- Multi-touch attribution (MTA) – A method where marketing actions are measured across a customer’s journey and a certain weightage is allotted to each stage, to discover value insights that each touchpoint has towards driving a conversion. Marketing campaigns apply a combination of online (multiple social media and business websites) and offline (print, billboards, streaming platforms, physical events) touchpoints to drive conversions. Measuring across these is challenging and employing MTA across the customer journey provides granular data for analysis. Customer journeys are complex as customers hop across various devices, platforms and channels before making a decision. Tracking their engagement is tricky, given data privacy concerns. Marketeers need to start tracking and monitoring KPIs and models, set up teams and use marketing analytics software while applying insights and continuously optimising marketing strategies. MTA is typically used on campaigns driven by digital budgets, A/B testing and automation platforms for campaigns.
- Unified Marketing Measurement (UMM) – this method uses a mix of different attribution models like MMM or MTA to arrive at comprehensive marketing metrics. This data is used to optimise campaign spend which in turn is expected to deliver effective conversions. Impactful UMM needs a unified analytics platform that can:
- Conduct data audits
- Continuously evaluate metrics for in-campaign optimisations
- Choose right data and models to feed into the platform
- Continuously discover the best models through a cycle of test and learn
MMM is relevant today and used alongside customer-centric analytics models to help organisations be aware of general broad-based patterns and trends over years.
Challenges to MTA are driven by lack of offline data applied in MTA models, limited visibility into external factors like seasonality and effective data wrangling given the complexity of data and models, where analysts land up spending a lot of time to make sense of the data.
The benefits of UMM include:
- Online and offline data visibility – combining MMM & MTA data
- Integrated data view
- Real time insights and optimisation to quickly pivot campaigns
- Personal and aggregate level data
Marketeers need to consider holistic marketing performance driven by key metrics such as brand perception data, in-campaign insights, granular consumer-specific data, and long-term aggregate data along with strategic and carefully planned implementation to drive growth using the right unified marketing platform, tools and teams.
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