Performing an Engagement Analysis on a model in LityxIQ lets you interactively explore how a marketing campaign will perform if the model were deployed to support it. The key question being answered is: with what percentage of the population should we engage in order to maximize the campaign's profitability? In addition, you can simulate the effects and tradeoffs of engaging with more or less than the optimal number.

The performance of the model itself plays an important role in the results of the Engagement Analysis because the stronger the model is (the better it is at identifying engagers/responders versus non-engagers/non-responders), the more efficient it will be when deployed to support the campaign. In other words, one model may allow you to make more successful engagements for the same total cost.

To begin with Engagement Analysis, select the model you want to analyze and click Evaluate & Explore -> Engagement Analysis from the Selected Model menu or the right click menu.

This will open a window allowing for interactively conducting the analysis. See below for explanations:

**1) Model Version/Iteration**- select the model version and iteration you would like to analyze.

**2) Interactive settings**

__Fixed Cost of Campaign__- Enter the fixed cost for the engagement campaign.__Cost of an Engagement Attempt__- Enter the cost of each engagement attempt. This could be, for example, the cost of an email, event, or direct mail piece.__Incremental Cost of a Successful Engagement__- Enter the average cost of a successful engagement attempt. This could be, for example, the average cost of a coupon or offer taken.__Value of a Successful Engagement__- Enter the average expected value derived from successfully engaging with a customer or prospect.__Total Population Size__- Enter the total size of the engageable population.__Population Pct Engagers__- The estimated percentage of engagers in the population.- Note that when you make modifications to any of these settings, the areas (3) and (4) described below change as well.

**3) Detailed Metrics section** - This table shows expected campaign metrics based on the value of the interactive settings and the selected model. These will change interactively as the interactive settings are modified, or the depth simulation value is changed.

__Selected Depth__- the depth of file that is currently active, and for which the metrics below are computed. The selected depth changes automatically to the optimal depth (maximal profit) when you make changes to the interactive settings. If can be modified to something other than the optimal depth using the Depth Simulation slider (explained more below).__Engagements__- the expected number of successful engagements given the current settings.__Missed Engagements__- the expected number of engagements that will be missed based on the current settings (those that would have engaged, but and engagement was not attempted due to the selected depth not being deep enough).__Total Cost__- the total cost of the campaign based on the current settings.__Total Profit__- the expected total profit of the campaign based on the current settings.

**4) Engagement Depth Analysis** - This graph shows how key campaign metrics change for differing targeting depths (as a percentage of the engageable population). The horizontal axis is the targeting depth. Further to the right reflects engaging with a higher and higher percentage of the population. The curves on the chart represent key metrics.

__Expected Profit__- the expected campaign profitability at each engagement depth. The highest point of this curve occurs at the depth where profit would be maximized.__Campaign Cost__- the total campaign cost at each engagement depth. Note that at Depth = 0, the campaign cost is the Fixed Cost that was entered.__Successful Engagements__- the number of expected successful engagements the campaign will generate at each engagement depth.__Missed Engagements__- the number of expected missed engagements the campaign will lose at each engagement depth.__Dark and light grey vertical lines__- This dark grey line will be placed at the depth where the maximal profit occurs based on the current model and settings. When you modify the depth using the Depth Simulation, the light grey line will also appear and be placed at the selected depth value as a visual way to compare to the optimal depth value.__Subtitle__- this will show, given the current interactive settings, the optimal engagement depth and the maximal profit that can be expected at that value.

**5) Depth Simulation** - While the objective of this analysis is to determine the optimal engagement depth for the campaign (which LityxIQ automatically computes), you have the option to see the effect of different depths on the expected campaign metrics. For example, maybe you want to see the expected cost and profit if you were to hit a certain number of successful engagements. Use this slider to change the depth, and see the result interactively in the sections (3) and (4) described above.

Note that you can also quickly compare one model version against another by switching the model version. All other settings will remain the same after you switch it, allowing you to see how the optimal depth would change, and how the different model version would affect campaign profitability and engagements.