Here are the strategies discussed in this section:
- Multi-location insights
- Drive business with localised content
- Build catchment areas with sub-location pages
- Drive growth through each location
- Replicate success for new business locations
- Long-term website authority & growth
- Implement PPC – and avoid competing campaigns
- Win customers without a business premise
Although we can’t name our customers, all of the strategies and examples provided in this section come from real-world campaigns we run for our multi-location customers.
#1: Multi location insights
The biggest asset you’ve got as a multi-location telegram number database company is access to performance data across every area. Instead of simply working with global data, you can gain insights from several, dozens or hundreds of different locations to spot trends, benchmark performance and differentiate each business location.
Even with the most basic data system in place, you can build a comparative picture of business performance across locations, including:
- Revenue
- Average sale value
- Sales volumes
- Top-selling products/services
- Search visibility
- Keyword search volumes
- Keyword CTRs
- Conversion rates
- Search visibility radius
- Local customer radius
This isn’t a particularly sophisticated
dataset but you can already identify which consultative selling: the guide to closing more deals locations are performing best (both financially and in search) and which ones are underperforming. From here, you can determine why certain locations are falling behind and optimise to improve results.
For our customers, we build a far more comprehensive dataset than the example above to develop a complete picture of business performance, which we can segment for each location or group of locations (top-performers, nearby locations, similar locations, etc.).
From this data, we can identify trends, similarities and differences across locations to understand why performance varies. These insights allow us to learn from top-performing locations, replicate success where appropriate and also understand why certain strategies won’t work for specific locations.
Taking this even further
we can enhance these insights with bgb directory competitor analysis to measure performance against local rivals. For example, we may see competitors also perform below-average in the same location and, then, determine whether this is simply a low-priority location or whether there’s anything we can do to dominate this particular area.
The next step is to pull in third-party data from external sources to provide more context to our first-party data and competitor analysis. For example, we might compare average sales values across locations with average salary data from ONS to identify locations that have room to promote more expensive offerings.
Or we might pull in historical and average rainfall data from the Met Office for each location and compare this with sales volumes. We can, then, use this data to develop a predictive model that incorporates weather forecasts to predict sales volumes and inform local content strategies and PPC campaigns.
We’ve barely scratched the surface of possibilities with multi-location data but the key point is to make full use of the data you have available. Local SEO is difficult for companies optimising multiple locations but the data you can produce has immense value – so take advantage of it.