Marketing as a social concept has a crucial role to play in creating socio-economically inclusive Smart Cities: Here is how

Projections show that urbanization, the gradual shift in residence of the human population from rural to urban areas, combined with the overall growth of the world’s population could add another 2.5 billion people to urban areas by 2050 (UN Department of Economic and Social Affairs, 2018). How all those citizens of cities live, and what their lives are like, will depend on important choices policy makers working with other stakeholders make today and in the coming years. 

Smart cities and the technology that underpins them has the capacity to improve citizens’ lives, with big data from multiple sensors a crucial component. For example, the city of Nanjing, China, has installed sensors into 10,000 taxis, 7,000 buses and 1 million private cars. The resulting big data transfers daily to the Nanjing Information Centre, where experts centralize and analyse traffic data and send updates to commuters on their smart phones to help improve their journeys. IBM is working with the city Rio de Janerio in Brazil to create a citywide-instrumented hub that integrates big data streams from thirty agencies, including traffic and public transport, municipal and utility services, emergency services and information sent by city employees and the public through their Smartphones. This single data analytics centre allows city officials to access real-time information, allowing them to make sense of and manage living in the city in the here-and-now, envisioning, and enabling future developments. Hypothetically, the mobilisation of big data citizen insight should provide the basis for transitioning Rio communities, with their extreme inequality and poverty, to a socio-economically inclusive and equitable places to live for all citizens. This is largely dependent on views on two distinct but related understandings as to what makes a city smart.

First, the notion of smart city represents a response to incoherent infrastructure design and urban planning of the past, with smart cities promising real-time monitoring, analysis and improvement of city decision-making. Ubiquitous computing and digitally instrumented devices are built into the fabric of urban environments, monitoring, managing and regulating city flows and processes in real time and producing big data and about citizens and their use of city utilities. Smart cities make use of Internet of Things (IoT) devices to fetch data and efficiently process it for implementation in specific locations. By inserting sensors across city infrastructures and creating big data sources — including citizens via their mobile devices — city policy makers are using big data analysis to monitor and anticipate urban phenomena in new ways. Smart city sensors and connected devices collect big data from various smart city gateways installed in a city and then analyse it for better decision-making in transport and communication infrastructure, security, educational and health developments. The results proponents say improve efficiency, sustainability of resources and citizen engagement. Criticism points to propagation of technocratic forms of governance, with projects like Songdo Ubiquitous City, South Korea, and Masdar City in the United Arab Emirates led by policy makers and corporates using big data in a way that can infringe citizens’ privacy. This smart city definition holds interest as it is a dominant paradigm, cutting against the smart city concept espousing the increased liveability of cities inclusive of all citizens.

Second, the notion of smart city can be viewed as one whose socio-economic development and governance is driven by innovation, supported by digital devices and big data and enacted by smart people. While smart cities instrumented with digital devices to produce big data and real-time analysis offers considerable potential, this technology in and of itself embedded in urban infrastructure does not make a city smart. It is rather how big data insights, in conjunction with human and social capital and wider socio-economic policy, can manage urban development that makes a city smart. The use of big data in smart cities, must enable citizens to participate fully in so-called knowledge societies. This notion of smartness is closely linked to the questions of economic and social equity. A smart city must be liveable, socially inclusive and must promote the wellbeing of all of its citizens. Smart city projects are big investments that are supposed to drive socio-economic transformation in areas such as transport infrastructure, education and employment and inclusive of traditionally deprived communities. This smart city definition positions participatory governance as key to creating inclusivity around urban issues (i.e. economic, social, and environmental), constructed through deploying big data to facilitate constructive interplays between policy makers, private and third sector and civil society.

Consideration of these two smart city perspectives, allow one to make a simple choice in terms of the marketing discipline and its relevance. On the one hand, smart cities are unique 21^st Century opportunities for marketing to position itself as crucial for corporate behemoths to develop value propositions for their technological offerings, such as artificial intelligence and analytics packages. On the other hand, smart cities are unique 21^st Century opportunities for marketing to position itself as a social concept to develop value propositions that harness technology for the socio-economic good of all citizens. Commercial marketing typically seeks to create value by understanding the various needs of diverse groups of customers, selecting relevant segments of customers with similar needs and targeting them with value propositions. Social marketing is the application of marketing principles to transform peoples’ well-being and social welfare. Social markets in a smart city, include a range of stakeholders involved in exchanges to improve or add value to citizens’ well-being and social welfare. Social marketing begins with understanding the barriers these stakeholders perceive to engaging in activities that improves, for example, employment opportunities in smart city communities. Social marketing also emphasises the importance of strategically delivering programs so that they target specific segments of smart city communities and overcome the barriers to them engaging with stakeholders to improve their socio-economic conditions. To achieve this, requires specific steps to be taken by smart city policy makers: 1) designing a governance platform to create collaboration between policy makers, private sector and local communities in smart cities; 2) deploying through this platform social marketing tools to mobilise smart city big data in segmenting local communities into groups with specific socio-economic challenges; 3) using social marketing and big data to promote inclusive socio-economic opportunities to these communities. While these steps may look straightforward, they will be continually buffeted by competing socio-economic needs of different stakeholders participating on the governance platforms. Creating value for these stakeholders that meets their needs through exchange of ideas and collaboration is facilitated by big data mobilised by social marketing.

This principle of exchange lies at the heart of reflexive governance as well as social marketing, with the recognition that there must be a clear socio-economic benefit perceived by stakeholders if change is to occur. The notion of targeted audience reflects the use of the customer orientation by social marketing. Social marketing in a smart city to achieve socio-economic change, needs to target specific, identifiable and reachable segments in relevant stakeholder groups. Such an approach can work with different target groups, for example at the community level segmenting by age, ethnicity and demographic profile. Part of the goal of such smart city engagement should be to understand the needs of all stakeholders and particularly local communities, to enable the resolution of competing goals. The compelling challenge for reflexive governance in smart cities is harnessing the power of big data using to resolve the competing socio-economic needs of multiple stakeholders. Changes of individual behaviour resides at the centre of this process, dependent on creating relationships and partnerships between various stakeholders. A key contention of my research going forward is that social marketing tools are crucial to mobilising big data insight to achieve this change in smart cities, through empowering reflexive governance.

Small Firms and Big Data

We all know the power and potential of Big Data to help businesses become more competitive. What is not so widely known, or discussed, is that Big Data threatens to create a deep divide between the have-datas and the have-no-datas. What I mean, is that the big corporations gain advantage by crunching the numbers while small firms are left to stumble in the dark. They are at a disadvantage to big competitors, which have the financial muscle to buy Big Data and expertise to exploit it. 

Over the past ten years I have worked with many small firms to help them source and make sense of Big Data. What have I found? ‘To use it’. That is the significant point when it comes to small firms and Big Data. Most often, small firms do not know how to use Big Data to gain competitive advantage. While cost of data is often prohibitive, lack of expertise to exploit the data is as, if not more, significant. 

Small firm owner-managers often rely on well-honed intuition to hold their own against data-rich, bigger competitors. In many cases they’re justifiably proud of their competitive intangibles—a gut sense of the market and the flexibility to change quickly. But is this sustainable and what are the implications for the UK economy? 

The UK Federation of Small Business states that at the start of 2020, there were 5.94 million small firms (with 0 to 49 employees), 99.3% of the total business. SMEs account for 99.9% of the business population (6.0 million businesses), three fifths of the employment and around half of turnover in the UK private sector. So, this Big Data challenge is a ‘big’ thing for small firms in the UK.

In my experience, once small firms are given access to Big Data the key to successful adoption is integration with their marketing and NPD process. This does not have to do away with their intuitive and flexible approach to understanding customers and competition in their markets. Rather, the data complements these essential small firm attributes. 

I have found that successful exploiters of Big Data are small firms that adopt, often for the first time, a considered approach to segmenting and targeting customers and positioning existing and new products to them. ‘Using the data’.

They were then able to envision new product innovations that precisely targeted what customers wanted, rather than reacting to competitors’ actions or pure gut instinct. One small-firm owner-manager said that Big Data had changed their ideas about how to grow its customer base. Another said, “Now we know precisely who our target customer is.”

So, what to do? Governments and Universities can play important roles in bridging the larger firm-small-firm Big Data divide, providing funds and expertise so that small firms can get access to, and learn to integrate it into their marketing and NPD. This is critical, given that COVID-19 is creating profound changes to how customers shop and what they are shopping for. If UK small firms are to respond, and survive, then access to and the capability to exploit Big Data will be key.

Geoff