Prioritize what to build next
Use Harvestr to build your own opportunity prioritization system
Valentin Huang avatar
Written by Valentin Huang
Updated over a week ago

Prioritization is key in product management.

That's why we have built a flexible yet powerful prioritization system to help you identify the most urgent customer needs and build the right features at the right time.

Your Product's interface in Harvestr

In Harvestr, the Product interface helps you get a central view of all the Discoveries you are working on. This view has two main purposes: reviewing your product roadmap and deciding what to build next by prioritizing Discoveries.

Add custom prioritization criteria for Discoveries

Discoveries have several criteria that can be used to evaluate and prioritize them. The default criteria are:

  • the pieces of customer feedback that have been aggregated inside of a Discovery

  • feedback volume

  • tags that can be used to flag must-have features and blocking issues for example

  • user segments that the Discovery impacts

You can also add custom numeric criteria to evaluate Discoveries more accurately and prioritize them according to your business and product criteria. 

Three types of fields can be added to Discoveries:

Numeric fields

Numeric fields let you assign an integer number to all your Discoveries.

Examples of numeric fields: 

  • total number of users impacted by a feature

  • number of hours required to develop the feature

Score fields

Score fields let you assign a score from 1 to 5 to all your Discoveries.

Examples of score fields: 

  • impact/ease scoring

  • evaluate to what extent a Discovery is aligned with your strategy

Financial value fields

Numeric fields let you assign an integer number to all your Discoveries.

Examples of numeric fields: 

  • expected additional revenue from a potential feature

  • the expected cost of developing the feature

Display/hide fields

You can choose which fields to display or hide by clicking the "Fields" button.

Build your own prioritization score

Once you have added all the numeric fields you need to your Discoveries, Harvestr takes the fields you created to compute a prioritization score that can be used to compare and rank Discoveries.

How is the score calculated?


First, you must give each field a weight from 0 to 100 according to how much each criterion should count in the final score. To change weights, go to "Manage numeric fields".

The "Score influence" column tells you how much each field weighs in the final score, relative to the others. The bigger the Score influence of a field is, the more it will affect the Score.

If a field has a Score influence of 80%, it means that this field accounts for 80% of the Score value.

Score value

In order for the Score to be easily understandable, we chose to always give you a number between 0 and 100. 

To do that, Harvestr first converts all your fields' values into a number between 0 and 100, for all your Discoveries. How? By dividing the field's value for a Discovery by the highest existing value for this field among all your Discoveries. This process is called "normalization".

For example, let's say I have a financial field where I put the expected additional revenue of a Discovery. One Discovery has an expected revenue of $10,000. Among all my Discoveries, the highest expected revenue is $100,000. Then, Harvestr would give the former Discovery an intermediary score of 10% (10,000 divided by 100,000) for this financial field. 

To calculate the final Score, Harvestr does exactly the same for each field. We then multiply each field by its weight and sum all these values, giving you a final score between 0 and 100.

To give you a complete example, let's say you have 3 prioritization criteria: A, B, and C.

You set the following weights for each criteria: Weight_A = 20%, Weight_B = 30%, Weight_C = 50%

You have the following list of Discoveries with the following values for each criterion:




Discovery #1




Discovery #2




Discovery #3




Discovery #4




Discovery #5




The value of the final score for Discovery #1 would then be equal to:

[20% x $10000 / MAX(A) + 30% x 10 x MAX(B) + 50% x 1 / MAX(C)] x 100

= [20% x $10000 / $15000 + 30% x 10 x 70 + 50% x 1 / 4] x 100

= 30

The score is always automatically calculated behind the scenes with the fields and weights you have defined. However, if you do not wish to use this score, you must hide it from the displayed fields. 

Filter and sort Discoveries to identify priorities 

Once you have set your custom fields and weights, you can use Harvestr's advanced filtering and sorting capabilities to extract a subset of Discoveries according to your needs and to prioritize Discoveries.

Filtering options

In Harvestr, you can filter Discoveries by tags, user groups, states, date created, last updated, last feedback, and numeric fields.

Date and numeric fields can be sorted in a relative way. You can for example filter Discoveries that have more than 30 feedback, or Discoveries that were created more than 14 days ago.

Filters can be added with "AND" / "OR" conditions. If we go on with the same example, you could filter Discoveries with more than 30 feedback AND were created more than 14 days ago.

Sorting options

Discoveries can also be sorted alphabetically and numerically according to the field you want to sort by.

Prioritize what to build next

All these filtering and sorting options can be combined to prioritize Discoveries and decide what you should focus on according to your own criteria.

Here are a few examples.

Prioritize trending feature requests from large accounts customers

  • filter Discoveries by tag "Feature request"
    AND filter by user group "Large accounts"
    AND filter by last feedback "is before one month ago" (for the trending criteria)

  • sort by feedback volume

Prioritize quick wins

  • give each Discovery an impact and ease score between 1 and 5

  • give a 50% weight to each of these criteria to compute the final score

  • sort Discoveries by the final score. The ones with high impact and high ease are your quick wins and will have the higher score

Prioritize Discoveries according to customer segments and a multi-criteria score

  • filter Discoveries by the user group you want to focus on, "Power users" for example

  • create and weigh fields of building a score that takes into account feedback volume, impact, ease, expected revenue

  • sort Discoveries by Score 

Use views to get the right information at the right time

A specific set of filtering and sorting options can be saved in a View. For all your Views, you can also choose to display Discoveries as a table or as a board.

Here are a few examples of Views you can set up:

Top feature requests view

  • type: list

  • tag filter: "Feature request"

  • state: all active states, exclude "Shipped" and "Will not do" Discoveries

Prioritization view

  • type: list

  • user group filter: chose only the user groups you want to focus on

  • fields: display all the fields you take into account for prioritization (user groups, numeric fields, score)

  • sort: rank Discoveries by Score to see priorities come on top

Roadmap view

  • type: board

  • state filter: display only active states, exclude "Shipped" and "Will not do" Discoveries

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