Understand the bigger picture of your data

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Diagnostic Dashboard

Attributes, events, sources & destinations

Insights

Check for any dips and spikes in the number of customer events and identified customers.

These numbers should broadly align with your customer engagement and acquisition strategy. E.g. expect a hike in numbers following a planned campaign.

In the case above we can also see that the number of identified customers overtime is increasing, as well as the number of events is increasing.  

Summarizes updates for customer entities for the last 7 days. Immediate updates happen each time when a new event arrives. Also when a customer entity merges with otheranother customer entity. Update for all customer entities happens from 1 to 7 days (depending on the use case). The most  of customers should be within the first bars, it is a warning if most of the customers are at the end of the chart (>96h).

In the case above customer data was not updated for a longer period of time, it is also suspicious that all results are 0, while at least one column should be filled, therefore it requires investigation.

Shows the number of customers that are identified on 1 through x sources. The higher the number of identified customers in the higher cross-across-data sources, the better the performance of the customer profiling process, and the better the quality of the customer profile output. 

The chart above shows that the highest number of customers (44.3 k)  is identified only in 1 source, while 31.2k customers across 2 sources., 1.4k (3 sources), 2.5k (4 sources), 236 (5 sources), 796 (6 sources), 42 (7 sources).

Shows the data sources that hold the highest/lowest amount of customers. This can help to see which data sources are the most helpful for collecting the data about customers. 

The chart above websites and Marketo collect the highest amount of customerscustomer data, while Net promotes score the lowest. 

Shows how many actions customers performed, type of actions performed and on which platforms your customer is engaging the most with your brand. 

In the example above we can see that the most popular is “Email received".

Shows how up to date events are.

The example above shows that the oldest event is "Contact form submitted on the web", 128 days, 18 hours. This time is extremely long, requires investigation.

Helps to evaluate the scale of the information about your customers across the data sources. In this way, you can evaluate what kind of data you can use to analyse, and determine which data source holds the highest amount of the information. You can evaluate the scale of the information about your customers across the data sources.  

In the example above, we can see that, for example, Google Analytics ID, Trade Desk ID are the most populated for the customers (45 000)