How the algorithm works

Making humanly impossible a common daily routine

The *why* and the *what* of pricing

Learn the basics of dynamic pricing

1. Why price?

Price is the monetary term that seeks to establish if the customer’s perception of value is equal to the seller’s perception of value.

If both parties perceive the value identically a monetary transaction happens.

If both parties perceive the value identically a monetary transaction happens.

2. What affects the perception of value?

The perception of value can shift for both the Supplier and the Customer

Seller (also called *Pricing Rules*):

- ease of selling a product
- available inventory
- breakeven point
- acceptable margin level

Customer (also called *The Price Elasticity of Demand*):

- poor presentation of the product
- competitors on the marketplace
- seasonality
- promotional campaigns
- disposable income
- price

3. What can sellers understand from the perception of value?

The variables affecting the customer perception of value together shape the **Price Elasticity of Demand**.

The Price Elasticity explains how much the customer's perception of value can be affected

by a slight change in price.

The Price Elasticity explains how much the customer's perception of value can be affected

by a slight change in price.

4. What the value perception has to do with the Elasticity curve?

In order to avail the Price Elasticity of Demand as a tool, the seller uses an **Elasticity curve**.

The curve shows the dependency of sales on price. It explicitly reveals how many items customers would buy at each price point on the curve.

A seller moves along the curve and chooses the price that maximizes sales velocity or revenue.

The curve shows the dependency of sales on price. It explicitly reveals how many items customers would buy at each price point on the curve.

A seller moves along the curve and chooses the price that maximizes sales velocity or revenue.

5. Why does it never work this way in practice?

The Elasticity curve is the best predictor of sales and revenue unless the perception of value changes.

If the perception of value shifts, the Elasticity curve reflects it.

If the perception of value shifts, the Elasticity curve reflects it.

6. What shows the Elasticity curve when the value perception changes?

CUSTOMER

**Poor presentation of the product**The product might be perceived differently because of low-quality imagery, unclear benefits, misleading application.

Enriching the product listing with high-quality content can lead to higher value perception and less price elasticity.**Competitors on the marketplace**Competition on the marketplace is arguably the most important criterion. If there are many competing products on the marketplace the customer would be tempted to make a buying decision purely off the price tag.

To stand out among competing products a seller would want to lower the price. The more competition there is on the marketplace, the higher is the price elasticity.**Seasonality**Seasonality refers to any visible sales cycle of the buying behavior. The perception of value increase when the cycle approaches. Think a Chrismas tree in the Christmas time.- Hourly seasonality reflects how much sales patterns in the morning and business hours are different to sales cycles in the afternoon.
- Weekly seasonality reflects how the buying behavior is different on business days versus weekends.
- Monthly seasonality mostly reflects the payroll cycles and the propensity to opt for inferior vs superior products as the disposable income shrinks.
- Yearly seasonality refers to holidays and to the change of weather when seasonal products become elastic.

**Promotional campaigns**Black Friday and 11/11 are known to drive the biggest surge in sales volumes. Customers know that there are gigantic discounts at online retailers. And they are prepared to find the best deal. Naturally, the price elasticity will be lower as all sellers strive to provide a bigger discount to enjoy larger sales volumes.**Income level**The lower is the income level the higher is the Price Elasticity of Demand.**Price**Individuals with higher incomes may view low-priced products with skepticism, suspecting them to be counterfeit, used, unpopular, or slow to sell.

Conversely, those with lower incomes often see expensive products as having superior quality and lasting longer.

SELLER

**Ease of selling a product**Think of R&D, competition, and the cost of advertising – all these factors reflect the ease of selling on a marketplace. Another way to call it is the barriers to entry. The lower are the barriers to entry, the more the seller is willing to compromise on price.

**Available inventory**Stock availability is an important factor in deciding on price. The lower is the stock level, the lower is the price elasticity for the seller. After all, it’s better to have slow-moving goods selling at a higher price, rather than having all stock sold out at low price at once.

**Breakeven point**The breakeven point is a deal breaker. The closer the selling price gets to the breakeven point, the lower is the acceptable margin level, and the lower is the price elasticity for the seller.

7. Why use the Elasticity curve in repricing strategies?

The perception of value is never the same. It shifts for both the customer and the seller all the time.

If sellers know the boundaries of the repricing strategies and if they know price elasticity, they can use it to their advantage, optimizing profit margins.

If sellers know the boundaries of the repricing strategies and if they know price elasticity, they can use it to their advantage, optimizing profit margins.

The *how* of pricing

Implement the basics of dynamic pricing

8. How do sellers set smart repricing strategies?

- BreakevenSet the breakeven price:
- Cost of goods at the manufacturer
- Cost of freight and delivery to the warehouse
- Cost of the marketplace including the affiliate fee and the last mile delivery fee
- Acceptable level of profit margin

- Ease of selling a productThe seller analyzes the competitive environment, the cost of advertising, and the original investments into the product (R&D and manufacturing). Doing so helps to adjust the pricing boundaries.
- Available inventoryThe seller assumes they have endless inventory at the warehouse. It is wise to operate under the going concern assumption that inventory is plentiful.
- Researching the elasticity curveOnce the seller is clear on their pricing range, they start analyzing the market response to their pricing strategies.

9. How do sellers research the elasticity curve?

The sellers systematically collect and analyze market data to fit the elasticity curve. The sellers collect information about how many items sell at different prices in one day. The information about sales velocity at different pieces then populates on the scatter plot of the two axes.

*The OX one shows the move of independent variable, which is Price.*

*The OY axis shows the respective shift of the dependent variable, which is QTY of items sold at each price.*

Once there are at least two dots on the scatter plot, the seller can visualize the most basic Elasticity curve.

Once there are at least two dots on the scatter plot, the seller can visualize the most basic Elasticity curve.

10. How do sellers make the elasticity curve actionable?

It is most likely that the two connected dots will have little descriptive or predictive value for the seller. Indeed, if there is no confidence in the outcomes, the seller must refrain from repricing.

Average metrics almost never work in prediction. The seller must apply more elaborate tools that help uncover actionable insights.

Average metrics almost never work in prediction. The seller must apply more elaborate tools that help uncover actionable insights.

PROBABILITY

Markets have always been volatile, and the online marketplace is no exception. As such, sellers must embrace the uncertainty of unstable sales.

Imagine that a seller collected two data points and estimated the average sales velocity. 5 units and 6 units sold in two consecutive days average out to 5.5 units per day.

It might also happen that the next week the seller records 7, 8, 9, 8, 5, 9, 10 sales per day. The average value of the last seven days is 8 units / day, while the average value of the first two days is 5.5 units / day.

Which one is correct? Neither. Which one is more probable? The aggregate one.

The first two days and the last seven days average out to 7.4 units /day. (5+6+7+8+9+8+5+9+10) / 9 days = 7.44 units per day on average.

This simple exercise gives the seller a powerful tool: the probability theory.

Imagine that a seller collected two data points and estimated the average sales velocity. 5 units and 6 units sold in two consecutive days average out to 5.5 units per day.

It might also happen that the next week the seller records 7, 8, 9, 8, 5, 9, 10 sales per day. The average value of the last seven days is 8 units / day, while the average value of the first two days is 5.5 units / day.

Which one is correct? Neither. Which one is more probable? The aggregate one.

The first two days and the last seven days average out to 7.4 units /day. (5+6+7+8+9+8+5+9+10) / 9 days = 7.44 units per day on average.

This simple exercise gives the seller a powerful tool: the probability theory.

It is impossible to tell the future. But the *more* sales data we collect from the past the *higher* is the probability to observe a certain event in the future.

VALUE PERCEPTION

Now that the seller knows about the probability of sales, they must account for the shifts in value perception as well. This is when it gets particularly tricky.

How does the seller know if the change in sales dynamics is attributable to the change in value perception and not to the market volatility?

They must apply the limitations that we discussed in the previous section.

*Chart: the chart shows average sales in the off-season and the peak season. Both series cover 30 days.*

*The blue one shows that there were 3 days of x1 sale per day, 4 days of x2 sales per day, etc. During the off-season there were 134 sales in total that averaged out x4.46 sales per day (+/- 1.56 sales).*

*The red one shows that there were 1 day of x4 sales per day, 2 days of x5 sales per day, etc. During the peak season there were 224 sales in total that averaged out x7.46 sales per day (+/- 3.16 sales).*

How does the seller know if the change in sales dynamics is attributable to the change in value perception and not to the market volatility?

They must apply the limitations that we discussed in the previous section.

The seller must answer the questions:

*Has the change in sales dynamics been statistically significant to be attributable to the change in value perception but not to the market volatility?*

11. How do sellers reprice with confidence?

Having applied the statistical methods, the seller gains an elasticity curve that factors in the volatility of each price point and the volatility of value perception.

The seller now can refer to the elasticity curve for each product and act upon it.

The more information the seller collects from the market each day, the more probable are the outcomes of each consecutive day, and the more confident they become about the predictive value of the elasticity curve.

The seller now can refer to the elasticity curve for each product and act upon it.

The more information the seller collects from the market each day, the more probable are the outcomes of each consecutive day, and the more confident they become about the predictive value of the elasticity curve.

12. How do sellers honor limitations?

PRICING RULES

The seller’s limitations are known as Pricing rules. These are the imperatives that plug into the pricing strategy. They define the floor price and the ceiling price that set the acceptable range for repricing. Also, the seller applies the pricing rule to the remaining inventory.

COMPETITION

The seller must know who they compete with for the money of their customers. Knowing the competitive environment helps to understand when the change in sales dynamics is attributable to the competitors pricing policy and not to other externalities. Finding the real competitors takes time and often results in misleading outcomes.

For example, a similarly looking product might not be a competitor because of the slight variation of the color. A similarly described product might not be a competitor because it appeals to other pain points. A product that ranks higher in search might not be a competitor, because the product owner simply decided to overbid with a more expensive keyword.

In fact, the only real competitor that the seller must keep on the radar is the one that consistently drives away sales. Finding all such competitors is important to succeed in pricing strategy.

For example, a similarly looking product might not be a competitor because of the slight variation of the color. A similarly described product might not be a competitor because it appeals to other pain points. A product that ranks higher in search might not be a competitor, because the product owner simply decided to overbid with a more expensive keyword.

In fact, the only real competitor that the seller must keep on the radar is the one that consistently drives away sales. Finding all such competitors is important to succeed in pricing strategy.

SEASONALITY

If the seller is fresh on the marketplace, they might have little knowledge about seasonality. Researching the competitors together with the trial-and-error approach is the best way to quickly garner market intelligence.

Once collected, the seller starts incorporating such knowledge into the pricing strategy.

Once collected, the seller starts incorporating such knowledge into the pricing strategy.

Dynamic repricing is a relatively new concept in e-commerce. It relies not only on the billions of data points that must be collected from the market daily but also on the transparency of data visualization.

- Those sellers who wish to
*reprice themselves*can use Holocene as a pricing analytics dashboard The dashboard visualizes pricing data in real time and provides actionable insights for savvy sellers. - Those sellers who wish to
*automate pricing decision*can use the AI co-pilot by Holocene that does the heavy lifting on the background.

1. Set up the pricing limitations.

2. Collect the sales data.

3. Understand the probability of each price point.

4. Incorporate market insights.

5. Validate the predictive value of the elasticity curve.

6. Reprice on each statistically significant change of sales dynamics.

2. Collect the sales data.

3. Understand the probability of each price point.

4. Incorporate market insights.

5. Validate the predictive value of the elasticity curve.

6. Reprice on each statistically significant change of sales dynamics.

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