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How can organisations choose the right data-analysis strategy to suit their personalisation needs?

How can organisations choose the right data-analysis strategy to suit their personalisation needs?

What issues should be font of mind when they evaluate and purchase solutions? We present a few guidelines and a market overview of technologies and types of analysis available.

The monetisation of customer relevancy through data-driven insights is essential for any successful marketing campaign in the digital economy. With the advent of social media, cloud computing, Internet of Things and mobile applications, data sources and use cases for marketing and communications professionals are proliferating. Companies can collect data on customer preferences, attributes, actions and more in order to, for example, anticipate demand, increase customer satisfaction and loyalty, as well as proactively capitalise on acquisition, upsell and cross sell opportunities.

Marketing and communication professionals who want to remain competitive must work in a hypothesis-driven manner to provide consumers and B2B customers the personalised messaging that has become a hygiene factor. In an interview with Travel Daily, Jonathon Wardman, Hilton’s vice president of customer relationship management talks about how his organisation uses data. Use cases Wardman mentions include smarter product design and matching customers and offers.

Here are some key enablers of the monetisation of customer relevancy through data-driven insights:

  • The citizen data scientist is usually a business specialist who has knowledge of data science, but is not a trained data scientist. The citizen data scientist is a bridge, making data science relevant and actionable to end-users.
  • Data visualisation evolved the delivery of insights to the end user and thereby has broadened awareness and interest in data. SAP and Google are examples of companies who offer data visualisation software.
  • Self-service business intelligence enables business end-users to work directly with data. Companies such as Tableau, Qlik and Microsoft offer self-service business intelligence platforms.
  • Cloud computing and cloud analytics offer abundant scalable technologies and products to users across organisations and geographies. The Adobe Marketing Cloud offers is an example of a customer intelligence solution.
  • Social media generates huge amounts of data concerning customer behaviour, preferences and attributes. Social media monitoring received a great deal of visibility with predictions made in the recent US presidential elections. Some social media monitoring tools include Hootsuite, Social Sprout and Salesforce’s Social Studio.
  • Internet of things (IoT) and Industrial Internet of Things (IIoT) have become a strategic imperative as sensors and connected objects are availing organisations new data sources and insights. Some platforms for IoT include AWS IoT platform, IBM Watson and GE Predix. 

As digitalisation of the economy advances, organisations will need to understand the universe of data available, as well as how to generate insight from their data. While marketers and communications professionals will not need to become data scientists or statisticians, marketing and communications departments will need to be able to build a data strategy and manage their data.

Data is only as useful as it is actionable. Beyond the critical step of defining meaningful key performance indicators, marketing and communications professionals will need to contextualise their findings, prove or disprove their hypotheses and create processes to turn insights into business transformation.

How can you structure your business intelligence solution?

Below is a four-level view of how a business intelligence stack could be structured. In parenthesis are a few examples of the technologies and/or processes to be found on each level.

  • Collaboration and communication (internal wikis, internal social media)
  • Analysis and visualisation (advanced analytics capabilities, visualisation, dashboards)
  • Data management (governance, data management)
  • Infrastructure (security, administration)

In the past few years, there has been a large amount of innovation in tools for collaboration and communication (Slack, SharePoint, Yammer) as well as the analysis and visualisation (Tableau, Qlik). Vendors who focus on data visualisation such as Tableau have gotten a large amount of attention. However, the integration of combinations of data sources in preparation for analysis and data management remains a challenge for many organisations. A number of niche and emerging players are bringing functionalities that make access to insights easier for the end-user to the market. For example, Sisense Everywhere integrates with Amazon Echo and IoT devices, enabling business users to consume insights through a two-way dialogue with chatbots.

What new insights can marketing and communications professionals gain from advances in the digital economy?

Social media monitoring has gotten significant media attention due to recent high-profile predictions pertaining to the US presidential elections. Huge opportunity exists for operationalising social media monitoring in sales, marketing and customer communication. In a study published by B2B research firm Clutch, almost three quarters of survey respondents say that the main benefits of social listening are improving their products and services (25 per cent), attracting new customers (24 per cent), and providing better customer service (21 Per cent).  Here are some definitions explained:

  • Social media listening can be described as the data discovery and data collection of activity on social media. Here analysts collect mentions, likes, hashtags and other important activities on social media.
  • Social media analysis refers to analysis based on data resulting from actions on social media platforms, collected through social media listening. Examples of such analysis are network analysis, influencer analysis and more.
  • Text analytics or text mining refers to analysing the actual language used in text. Examples of such analytics are sentiment analysis, natural language processing – and word clouds.

How can social media monitoring benefit marketing and communications professionals?

  • Combining social media analysis with other data and information sources for actionable strategic insight. Social media data is interesting because it is data based on actual human behaviour. Its true potency can be harnessed when it is meaningfully combined with a multitude of data sources.
  • Bringing management to the next level using analytics from collaboration tools and other web-based platfroms, both external and internal. While social media usage and analytics is widely known in the private sphere, there is opportunity to understand how groups of individuals within organisations interact – or can interact.
  • Understanding demographics, politics and social trends. Through social media platforms, researchers can access vast amounts of data based on actual activities of large amounts of people.

Internet of Things enables organisations to avail themselves of tools such as real-time analytics and geospatial location intelligence. Manufacturing, transport and retail are examples of sectors that been investing in in IoT, IIoT and spatial analytics. Smart manufacturing, smart logistics and use of sensors in predictive maintenance are some leading areas of investment. For marketers, real-time analytics and geospatial location intelligence allows location based marketing to help organisations optimise their customers’ omni-channel experience . Here are some definitions:

  • Internet of things is a system where physical things have IP addresses and are connected to each other through the Internet. These devices can identify and communicate with each other.
  • Industrial Internet of Things is use of the internet of things in an industrial setting. The vision for the Industrial Internet of Things is that sensor data, machine-to-machine communication and automation technologies together with cloud technology, machine learning and other big data technology will enable smart machines to work in a more flexible and accurate way.
  • Location based marketing is the triggering of a marketing or advertising event based on location. Messaging involved in location based marketing often involves alerts delivered to a smart phone.

How can the Internet of Things benefit marketing and communications professionals?

  • Linking customer insight to smart processes to provide a comprehensive, customer experience on an industrial scale throughout the entire customer journey- both in the virtual and physical world.
  • Managing live experiences is one use case that retail and event management organizations are investing in. With the use of spatial analytics and IoT, organisations can create a more comfortable and enjoyable live experience for individuals by better understanding crowd flow, controlling temperatures and other enhancements that have until now been done by manual processes or even gut feeling.

Analytics initiatives begin and end with the end-user

An analytics initiative needs to be plugged into the overarching strategy of the organisation and the end-user’s objectives if acceptance of the validity of the output and integration into the organisation’s workstream is to take place. Moreover, insights and data need to be consumed in a way that is both understandable and actionable for the business user and the organisation. Scalability and delivery of actionable insights across functions –and often across geographies - is critical to the success of any analytics initiative. Insights that can’t be accessed cannot be used. 

Data is only as valuable as the business impact it generates.

Elizabeth Press

Elizabeth Press is founder of D3M Labs, a consultancy that empowers organisations to cultivate strategic advantages by monetising big data and advanced analytics. Organisations Elizabeth has worked with through D3M Labs include Mondelez, Betahaus, IAV and the German Foreign Office. Elizabeth has been a mentor in the field of business intelligence at accelerators in Berlin and the New York Metropolitan area, as well as the ReDI School of Digital Integration. As an intrapreneur at Dell, Elizabeth built up and managed advanced analytics functions globally. Before Dell, she worked in top-tier strategy consulting and quantitative finance.