A while back I ran across a developer coding for the upmarket. It took me a while to recall what an upmarket move was. Geez. And, when you’re talking upmarket, there is a down market. I don’t think in those terms since they are late main street and the horizontal phase issues. Not my game.

### Downmarket

I decided to look at them from the standpoint of the technology adoption lifecycle, so I drew two figures to take a look at them.

I drew the downmarket case starting with the technology adoption lifecycle (TALC) as a normal of normals. The company is in the late mainstreet phase. This is usually where a company builds a downmarket strategy. Companies in this phase are on the decline side of the TALC. Growth really a matter of consuming the market faster and reaching the end of the road, the death of the category sooner. Growth is a stock market trick. Going downmarket is a way to grow by actually increase the size of the population that the company is facing.

I labeled the baseline of the TALC “Former. ” Then, I drew another line under the TALC. This line should be long enough to contain the population that the company is moving downmarket to capture. I labeled this line “Planned.” Then, I drew a standard normal to sit on this new line extending from the original normal. I did not normalize the new normal.

The current market is a subset of the new down-marketed market. The new market need not be centered at the mean of the current market. The population will be new so the mean and standard deviation could differ. The standard normal view of the TALC assumes a symmetrical distribution. This need not be the case. Having two means do make a mess of the statistics. It might not look like a binomial. It will exhibit some kurtosis. The speed of the efforts separating the means will take time and planning. If the company is public, it must provide guidance before making such efforts. Don’t switch before providing those projections to the investors.

I went with have one mean in the figure.

The downmarket effort starts with a making the decision. The decision will require some infrastructural changes to the marketing and sales efforts at a minimum. It will also require some UX and code revisions to give the downmarket user relevant interfaces. Simple things become much harder when the user doesn’t have the funds they need. The cognitive model may differ from that of the upmarket. These problems may or may not be an issue with your software. The decision might be made across products, particularly in a company organized around their bowling alley. That could mean that this downmarket might be a permanent element across all products.

After some period of time, the decision to move downmarket will become operational. Sales may continue in the current markets as other sales efforts address the new downmarket or the current market might be deemphasized or delayed. I removed it. I color coded the lost earnings in yellow and notated it with a negative sign (-). I color coded the gained earnings in green and notated it with a positive sign (+). The gained earnings are dwarfed by the lost earnings as the scale of the market grows and subsequently hits the first scale constraint. Then, the downmarket move will stop until the current population and projected population can be supported. Efforts to support the increase in scale can start earlier before the scale constraint generates a crisis.

Beyond the first scale constraint, the gains begin to drown the losses. Then, the next scale constraint kicks in. Once again the downmarket move will stop until the infrastructure can support the needs being generated by the downmarket move.

Beyond the second scale constraint, the losses dry up and the gains continue out until the convergence of the normal with the x-axis happens, aka the death of the category. Another managerial action will need to be taken to further extend the life of the category.

Notice that I moved the baseline downward beyond the second scale constraint. I labeled this “Overshoot.” I did this to make the losses look continuous. Initially, the curve sat on the original downmarket baseline, but this gave a sawtooth-shaped curve. I’m unsure at the time of this writing which representation is better. As shown, the convergence with the baseline of the normal shows up on the “Overshoot” line.

Pricing will drive the speed of the downmarket realization. Pricing might impair the downmarket move. The net result of the downmarket move will be an increase in seats, which turns into an increase in eyeballs, financial results will depend on price, policies, and timeframes, and an extension of the life of the category.

### Upmarket

In the TALC, we usually start in the upmarket and work our way to the downmarket as we move from early (left) to late (right) phases, from growth to decline. Hardly ever does a company move upmarket after being a lower priced commodity.

Here I started with the TALC again. I selected a target population, a smaller population, and drew a horizontal above which would represent the upmarket. The upmarket as a horizontal slice across the normal is shown in yellow and gold. Renormalizing that gets us the green and orange normals. The purple arrow behind the normals provides an operational view as sales grow the eventual standard normal shown in orange. The zeros convey how the market is not growing. The higher prices of an upmarket might shrink the size of the market.

When converting an existing market to a higher price, we can consider the market to be Poisson, eventually a kurtotic normal shown with the gray normals, and finally a standard normal without kurtosis. The figure skips the Poisson distribution and begins with the kurtotic normal. Normals with small populations are taller. They shrink towards the standard normal. When a normal is kurtotic it exhibits a slant which disappears as the kurtosis goes away.

I called all of these changes in the size, shape, and slant of the normal the “Price Dance.” This dance is illustrated with the purple arrows. Once the standard normal is achieved, kurtosis risk is removed. As the standard normal gains sigmas, the risk is reduced further.

The Poisson distribution representing the initial sales at the higher price puts the product back in hyperbolic space. Once the single sigma, standard normal is achieved, the product is in Euclidean space. From the single-sigma standard norm, the sigmas increase. That puts the product in spherical space where the degrees of freedom of strategy and tactics increase making many winning strategies possible. In the hyperbolic space, those degrees of freedom are less than one. Euclidean space has a single degree of freedom. This implies that the Euclidean space is transitory.

The net result of the upmarket move will be an increase in revenues depending on pricing, The number of seats will remain constant with optimal pricing, which in turns leaves eyeballs unchanged. Upmarket moves shorten the life of the category.

### Summary

Downmarket moves take a lot of work, more work than an upmarket move. In both cases, the marketing communications will change. Upmarket moves get you more dollars per seat, but you would have to be selling the product. The number of seats does not change or falls with an upmarket more. Downmarket moves get you more seats, more eyeballs, and given pricing, more revenues if any are independent revenues from eyeballs. Downmarket moves extend the life of the category/product/company. Upmarket moves shorten those lives.

Downmarket and upmarket moves are orthodox strategies and tactics. Talk with your CFO. I’d rather keep the lanes of my bowling ally full.

Enjoy.

November 17, 2017 at 2:16 pm |

[…] via Upmarket and Downmarket — Product Strategist […]