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Studies point out Which retail units capture only 86% of your sales potential
This is because brands don't even know their potential and they don't fully understand the profile of the regions they serve.
Some companies do their planning in spreadsheets, which completely ignore the spatial relationships between phenomena and do not provide a vision of sales potential.
This is the role of Geomarketing in organizations, to indicate the size of the opportunity and how it is structured.
Analysis on maps surpasses spreadsheets because it represents the geographical phenomena that affect the lives and decisions of the public.
Take a look at this example below:
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In it, a particular network sees its sales grow as the average family income in its surroundings increases.
However, when the average income is very low, sales plummet, a sign that families may completely disregard that offer or seek more affordable alternatives.
In the same way, when the average income is very high, sales stop growing, a sign that families there are looking for even more sophisticated options.
The stretch of the graph where sales reach their ceiling could be considered the network's optimal track, the audience profile most likely to buy.
Would they be the stores A Of a ABC curve:
- A-stores account for 60-80% of the chain's revenue
- B stores account for 15-30%
- C stores keep the rest
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The expansion of this network should target regions with these characteristics.
But that's not what happens.
Spreadsheets If you stop in time, you prefer to expand based on comparable sales metrics between the chain's stores:
- Sales per m²
- Same Store Sales (something like sales per m² over time)
- Frequency of purchases (tickets)
- Retention (sales to the same customers)
- Average sales amount (average ticket)
- Shopping basket (grouping items by ticket)
- Inventory turnover and disruption (availability of products for sale)
- Breakeven point (how many sales the store has to make to cover its costs)
- Profit (how many sales the store makes after covering its costs)
- Profitability (profit on investment) at the opening of that store
These indicators are incredible and very useful, but they shouldn't guide expansion.
Like what we saw in the graphic above, the expansion must be guided by sales potential.
However, our friends Spreadsheets They are enchanted when the sale per m² is high, when the Same Store Sales shows growth, with more sales on higher tickets.
For them, so many positive indicators are sufficient justification for opening a new unit in the region.
Now look at the quadrants described in the matrix below:
In it, we can find different scenarios of Same Store Sales and Profitability.
The quadrant of Much higher than expected results Will show us a good one Same Store Sales and adequate Profitability.
The region's potential is low and the store's good performance is almost a miracle. Opening a second store there will ruin profitability.
In the next quadrant, Well, as expected, all indicators will be healthy, and there may even be room for more stores, but there is still a risk of jeopardizing Profitability.
On the bottom line, the indicators will be bad, but on the quadrant It has potential, poorly worked, sales metrics will point to non-investment and the network will stop exploiting this growth opportunity.
Finally, the lack of market vision may lead the network to open units in regions of low potential, something that will only be perceived by Spreadsheets a long time later.
At that time, the investment in opening and maintaining a low-potential unit will have been lost and the sunk costs will dilute the overall profitability of the network.
We hope to have demonstrated that expanding using internal metrics is totally wrong in 75% of the scenarios and still poses risks for the remaining 25%.
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A store that sells well in a region with low potential has something to teach us, This is the learning zone.
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A store that sells poorly in a region with high potential has something to learn, This is the execution zone.
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A store that sells well in a region with good potential is the network standard, scenario that must be replicated.
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Who opened a store in a low-potential region?
With the new mapping feature, you can map your stores and understand what quadrants they are in.