Digital Marketing and Data Analytics

  • 13 Pages
  • Published On: 15-12-2023


A market research survey conducted to determine customers’ preferences based on products customisation, type of sales campaign, and pricing. In the survey, the responses were ranked to reflect the customers’ preferences level. For instances, in campaign level, level 9 indicate preferences of social media (modern communication approach) while level 1 indicating preferences of using traditional communication methods in product campaign. Similarly, level 9 in price category indicate the consumers are highly conscious with the prices while level indicating little interest in prices.



For the purpose of this study, a marketing survey was conducted. The researched areas were respondents preference of the products, sales campaign, and price consciousness. The respondents were required rank their preference on a scale of 1-9 on difference research variables. For instances, in sales campaign, the preferences of the marketing campaign listed with preference for a traditional media ranked 1 then scale moving to highest preferences, 9, being modern communication approach. In this case, social media. Fifteen respondents took part and completed the marketing research survey.

Table 1: Data from the marketing survey Table 1: Data from the marketing survey


The data on product preference indicate the consumer’s ranking varied from 1.00 to 9.00, similar to campaign approach (1.25 to 8.50) and price consciousness lowest being 1.50 and highest ranked being concerned with product prices standing at 8.75. Using the minimum, maximum, and median values of the respondents’ responses, a starting point clustering of the points. Using the minimum ranking value for the product (1), maximum (9), and median being 5, three segments were identified using the respondents start points.

Table 2: Initial segments labelled 1, 2, and 3 Table 2: Initial segments labelled 1, 2, and 3

As shown in the Table 2, segment 1 had 3 respondents, while segment 2 had 7 respondents, and third segment had 5 respondents. Across the three segments, the respondents shared a common perspective on the products. The segmentation k-means clustering used in identifying the shared values among customers follows an iterative approach that divides the unlabelled dataset into k different clusters –in a way that each dataset belongs a group, mostly one group that share similar properties.

In the revised mean, some of the respondents were decluttering into a different segment. For instance, respondent 3 who previously had been in segment 3 was shifted to the cluster 1. Distance from revised mean- Sums the squares of the differences in the corresponding ranges or arrays enables placing a customers in a particular clustered. From the table, clustering saw respondents who held moderate preferences across the three variables, that is, price sensitivity, sales campaign, and product customisation were grouped into segment 3. For a marketer, using the shared commonness among the customers in a given clustered, for instance segment 3, can develop a marketing strategy tailored specifically aligned to these shared elements among the individuals in the group.

Table 3: Revised mean clustering segmentation

Segmentation concept

In relation to consumers, Camilleri (2018) described segmentation as a practice of dividing a customer base into groups of individuals who share similar attributes. According to Aljukhadar and Senecal (2011), it the technique allows market targeting by identifying and operating in a market that is most attractive to the business as well as in a region that customers have similar needs and preferences. Although segmentation can be based on number of factors, demographics segmentation attributes that include sex, age group, education levels, and socioeconomic variables are commonly used. Segmentation can be classified into first geographic segmentation. This captures a geographic region in which a particular consumer bases resides. In this approach, a company can tailor a product and marketing campaign in line to the local purchasing power, socioeconomic factors, regulations, and general consumer behaviour in a given region (Rutigliano, 2019). Secondly, the demographic segmentation. The demographic grouping outlines the consumers attributes based on the shared characteristics such a age group, education levels, sex, marital status, employment, and income. According to Camilleri (2018), demographic factors have a significant influence on the underlying living standards, consumption rate, and consumer purchasing behaviour. In addition to being predisposed to having less purchasing power, youth particularly individuals aged between 18 and 25 years tend to be influenced by their peers and currently, social media influencers in making buying decisions. While demographic with higher education levels, tend to rely on an informed data in making decision. Thirdly, psychographic segmentation. This segmentation incorporate grouping of consumers based on lifestyle, values, and beliefs. Understanding the values held by a group of individuals is significantly important to marketer in developing strategy (Rutigliano, 2019). For some customers preference classic products while other driven by trends. Lastly, behavioural segmentation characterised by shopping and purchase behaviours.

Building from this by knowing that segment 2 customers are significant conscious by pricing but rather hold significant preferences to traditional sale campaign and timeless classics, allow an organisation to focus resources on parts of a market where the business have a higher probability/chance of success- allows growing share in markets or to ride the wave’ of fast-growing segments. These cohort, who can be classified as baby boomers/older generations are not inclined to use and conform to changes in communication, such as using social media unlike customers in a younger generations segment. Similarly, segment 2 indicate a market can adopt a moderate sales campaign, pricing not to be low or too high, and product characteristics to lie in between the classics and customised products. With these insights, a marketer can develop focused products on the needs of customers –in a given segment. Ideal in marketing market mix more effective- better targeting of promotion and developing a marketing strategy

Price optimising Enhancing competitiveness of a product/organisation Brand awareness Acquisition & Retention Increases revenue & ROI

Case 2: Ecommerce sales


Bluebird marketing campaign compose of three strategies. First, Campaign A involving regular online newsletter, secondly, a Campaign B that is a pay per click (PPC) strategy through search engine marketing (SEM), and lastly, Campaign C in which the company promotes its products through its social media platforms (Facebook and Twitter). In line to the segmentation done, the company deploys the three marketing campaigns across the clustered groups. Notably, based on the unique characteristics and attributes held by each segment, the sales across the group differed. For instance, Segment 1 had a high sales percentage of the groups owing to the groups lifestyle and purchasing behaviour in addition to high preference of using social media in accessing marketing and sale promotions. In contrast, the third segment had the lowest sales which is attributable to inclination to prefer traditional sale campaign and timeless classics as well as being price conscious. These older generation cohort tend to be conservatives and not impulsive buyers based on current trends rather it is what they goes with their taste. Therefore, understanding the features and values held by each group, launching a marketing strategy tailored specifically to take advantage of shared characteristics increases the effectiveness of a marketing campaign. As shown by Table 2.1, with a focused campaign across the three segments, the company is able to record higher sales from segment 1 then followed segment 2. The grouping customers based on their preferences enables committing more resources (budget) to a specific campaign targeting a particular group rather than throwing everything on the wall and hoping some campaigns will stick.

Table 2.1: Total segments and total fiscal year

Case 3: Performance metrics

Bluebird’s competitor, The Boot N’ Shoe Co manufactures and sell customised shoes in the same market. The table 3.1 shows comparison of the two companies, and

Using the data from the Table 3.1, the analysis will be drawn around the market approach and growth performance metrics and brand and customer development metrics. Theoretically, brand equity is subject to number of variables that include brand awareness, perceived value relating to a product, brand association such as quality, lifestyle, and social status, consumer brand loyalty, and willing to pay a price premium (Farris et al., 2016; Shabbir et al., 2017). In order to have an in-depth understanding of their respective comparative competitive advantage, the two companies need to have an insight into their brands.

Brand equity Index = Effective Market share * Relative Price * Durability


Comparison of Bluebird and The Boot N’ Shoe Co performance Metric

From the findings, Bluebird Footwear has a higher brand equity index compared to Boot N’ Shoe Co (0.1078 to 0.054). Moreover, the contribution of the Bluebird Footwear’s customers to the company is significant higher (£372,000 to £110,000). It depicts the long-term financial value the consumer injects to the company. Therefore, the company need to invest more on the acquisition of customers and importantly retention. Evident by returns on marketing investment, the Bluebird higher performance is pegged on the customers’ perception on the brand and effectiveness of the marketing strategy adopted. As such, the company should focus more inject more on the marketing and retaining consumers.

Case 4: Pricing

Plan for Bluebird’s new customisable product line. Originally, the company had set the product prices to £250. However, in order to attract more consumers by offering cheaper options particularly those that are price conscious require drawing a strategy based on invested cost and forecasted returns. Notably, for a product to have a positive return, it has to take into account the cost of producing under the fixed and variable cost as well as the marketing and customer retention cost over a specified time. However, considering of the consumers values and preference is also fundamental. As mentioned above, consumers have different preferences and values shaping their purchasing behaviour and continuing using the same brand. Fundamental to this is accommodating the consumers with different preferences.

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Table: Data

Bluebird’s Product launch data

Table: Pricing Calculations

Bluebird product Markup/Cost Pricing and Target Return Pricing

From the table 4.2, the unit cost of the product stands at £52. With percentage markup of 70% means the company returns per product stands at £88. However, this, to consumers who are price sensitive (segment 1), might be relatively high. Setting the return on investment at 50% means the product prices would reduce from £250 to £240 making a justifiable returns covering production costs, operation cost, and return on investment. Nevertheless, disadvantage to this approach is failure to offer competitive prices guided by competitors’ pricing as well as not giving marketers to operate efficiently.


Aljukhadar, M. and Senecal, S., 2011. Segmenting the online consumer market. Marketing intelligence & planning.

Camilleri, M.A., 2018. Market segmentation, targeting and positioning. In Travel marketing, tourism economics and the airline product (pp. 69-83). Springer, Cham.

Farris, P., Gregg, E., Chinn, B. and Razuri, M., 2016. Brand equity: An overview.

Riefler, P., Diamantopoulos, A. and Siguaw, J.A., 2012. Cosmopolitan consumers as a target group for segmentation. Journal of International Business Studies, 43(3), pp.285-305.

Rutigliano, K., 2019. Council Post: Prioritize Your Customer Segmentation In Digital Marketing Campaigns. [online] Forbes. Available at: [Accessed 29 April 2021].

Shabbir, M.Q., Khan, A.A. and Khan, S.R., 2017. Brand loyalty brand image and brand equity: the mediating role of brand awareness. International journal of innovation and applied studies, 19(2), p.416.

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