Today, 75% of couples have two incomes. In this context, where time at home has decreased, household cleaning services are thriving!
However, competition is fierce: these companies are multiplying, technology is automating certain cleaning tasks, and not all households can afford cleaning services. The challenge lies in the ability to stand out in a competitive market and effectively target potential households for marketing campaigns.
Challenges
The main challenge for cleaning service companies is to gain visibility among households and position themselves as the ideal solution for their cleaning needs. With growing competition in the industry, it’s essential to develop a targeted and effective marketing strategy to reach the right customers at the right time.
With the rise of social media, the best way is often to create targeted campaigns on Instagram or Facebook. To reach other types of clients, one could also consider physical marketing campaigns (such as flyers in mailboxes). However, competition for creating targeted campaigns is also growing. To be more efficient and cost-effective, the goal is to target specific geographic areas based on the service area of the cleaning company.
Why is this so important?
For cleaning services, it doesn’t make sense to target low-income couples without children, for example. However, if you don’t know your area well, it’s possible to send this type of online or physical ad to the wrong audience. To be more precise, one target could be elderly people who no longer have the energy to handle house cleaning. If you only run a social media marketing campaign, it’s unlikely that these elderly individuals will see your campaign. Worse, if you target a specific neighborhood where the majority of residents are elderly, you could risk a complete flop!
Thus, we see the importance of knowing the terrain better to conduct a successful marketing campaign! This helps de-risk your campaign and makes it more effective in reaching your core target.
The Solution: CIV.GEO for Marketing Campaigns
To tackle this challenge, cleaning service companies can adopt a strategic marketing approach based on data analysis and market segmentation.
Here are a few target segments:
- Dual-income couples with high incomes
- Elderly individuals with reduced mobility
- Companies in the service sector
For example, in Magog, there is a higher concentration of people aged 35 to 54 around Magog Hospital. Zooming in, there’s a higher concentration of high-income households from the intersection of Stanley Street and Hall Street to Ruisseau Park. For high-income households, we consider households with incomes over $60,000.
Additionally, analyzing residents’ commuting times, there’s a high concentration of people whose workplaces are over 60 minutes from home. Out of 1,245 residents, only 80 work from home, confirming the potential for targeting this market.
This example could be further refined by examining discretionary income — analyzing people’s ability to afford services after spending on basic needs (food, rent, insurance, internet, and electricity). Analyzing discretionary income is increasingly relevant. For instance, for the same income, a new resident might pay up to 50% more in rent than someone who has lived in the same place for five years. For average rents of $1,500, this can mean a $500 monthly difference.
Thus, a cleaning company could expect a better return on investment for its marketing campaign by targeting this area for active, dual-income individuals with high incomes who work far from home.
To perform this client segmentation, there are several open data solutions. For example, Québec Open Data provides datasets for identifying neighborhoods with the worst sanitation conditions. This gives a good indication of needs. Then, Statistics Canada can help identify the demographic composition of these areas with the greatest need.
Precise targeting like this takes time. One way to reduce the time spent is by avoiding the need to manually search for all this data. To give an idea, gathering this information typically takes 10 minutes per area. Just comparing the 30 areas that make up Magog would take an estimated 5 hours.
Additionally, there are comparisons between data and analyses of these areas. Since these areas are not isolated, they need to be analyzed in the context of neighboring areas. For example, if an area (often spanning 1 to 5 streets) is ideal, neighboring areas may have completely different compositions. This requires assessing both the area’s and its neighbors’ relevance, taking at least 2 to 3 additional hours.
In total, using open-source data may be useful, but it would cost around 8 hours. For a trained person earning $35 per hour, this amounts to a cost of $280.
To avoid these costs and inconveniences, we offer Civ.GEO to help companies target their marketing campaigns. Instead of spending 8 hours analyzing 30 areas, our map allows for comparison and selection of ideal zones in just 5 minutes. For 50 areas, we offer a rate of $250, which is cheaper than the manual effort.
Result
Analyzing data to optimize a marketing campaign is certainly an effective way to maximize its ROI. This cleaning service company was able to more precisely target geographic areas for its social media marketing campaign and for flyer distribution. Using Civ.GEO also saved them time and money on data collection.
Social and Environmental Impact
By better targeting its areas, the cleaning service company can directly engage with a population that needs its services. For field visits, it optimizes travel routes and reduces the number of flyers, thereby reducing its carbon footprint.
