Trend Solutions
Updated
Trend metrics provide the daily level performance of posts. Respective Channel APIs provide only lifetime value i.e. the total number of say impressions on a post. There are multiple instances when data from the API could fail for a singular day, in this article we will cover how we adjust trend metrics and the nuances around those.
Potential discrepancies that might show up
Sprinklr has observed sometimes that lifetime value of metrics like impressions, video views, etc reduce over a period of time. This results in negative values of impressions which is not possible.
Date | Facebook Post Impressions | Facebook Post Impressions Trend | Comments |
1-Jan-19 | 100 | 100 |
|
2-Jan-19 | 500 | 400 |
|
3-Jan-19 | 1000 | 500 |
|
4-Jan-19 | 2000 | 1000 |
|
5-Jan-19 | 4000 | 2000 |
|
6-Jan-19 | 3900 | -100 | Lifetime value decreased by 100, hence resulting in negative trend values. |
In case, Sprinklr is unable to fetch data from respective APIs due to intermittent errors in API or inactive account, then the combined performance gets reflected on the date when Sprinklr makes a successful API call resulting in inflated numbers.
Date | Facebook Post Impressions | Facebook Post Impressions Trend | Comments |
1-Jan-19 | 100 | 100 |
|
2-Jan-19 | 500 | 400 |
|
3-Jan-19 | 1000 | 500 |
|
4-Jan-19 | 2000 | 1000 |
|
5-Jan-19 | - | 0 | Unable to fetch data from API or inactive account. The trend is set as 0. |
6-Jan-19 | 6500 | 4500 | Inflated numbers as a trend include a number of impressions received yesterday. |
Note: When a historical backfill request is raised, all the performance numbers for old posts get reflected on the date when backfill was run. This results in a huge spike in numbers.
How Trend Data is Generated for Missing Dates or Negative Values?
Negative Values
Date
Facebook Post Impressions
Facebook Post Impressions Trend
Comments
1-Jan-19
100
100
2-Jan-19
500
30
These data points are generated using a curve-fitting algorithm.
3-Jan-19
1000
50
4-Jan-19
2000
60
5-Jan-19
4000
70
6-Jan-19
400
90
Missing Dates: Whenever data is fetched from API, Sprinklr generates the missing trend records for a date between last trend date and current date. The same curve fitting algorithm is used to generate data for missing values. For example, if a post was published on 1-Jan-19 and our API call failed on 12-Jan-19 and 13-Jan-19, Sprinklr would create trend records for missed records using a curve fitting algorithm when the latest data is available on 14-Jan-19.
Date
Lifetime Value
Trend Value
Comments
1-Jan-19
13242
13242
2-Jan-19
14483
1241
3-Jan-19
17724
2424
4-Jan-19
20148
1000
5-Jan-19
21480
1332
6-Jan-19
22456
985
7-Jan-19
23029
564
8-Jan-19
23484
455
9-Jan-19
24174
690
10-Jan-19
24488
314
11-Jan-19
24730
242
12-Jan-19
-
0431
Unable to fetch data from API, hence trend record doesn’t exist.
13-Jan-19
-
0401
Unable to fetch data from API, hence trend record doesn’t exist.
14-Jan-19
25943
1213381
When Sprinklr fetched the latest value from API and saw that no trend data was available for previous days, generate values using trend data.