Introduction:
This article deals with a detailed explanation regarding Investors & Investment insights, which can be requested quarterly or semi-annually. These insights are presented in a comprehensive PowerPoint presentation that analyzes a defined period based on various groupings, once per lead, and once per investment path. For instance, it doesn't just look at the age distribution of leads by frequency but also by conversion rate and invested volume per age group. This can provide valuable insights, particularly from a marketing department's perspective, to draw conclusions for more efficient advertising.
In addition to interesting charts and notable trends, the added recommendations can facilitate the interpretation of the PPTX.
In the following, we will demonstrate the interpretation of this PPTX using a random example and timeframe:
Dataset:
Grouped by started investment process
| Investment_id | invested | Investor_id | CC | volume | product |
| 1 | 0 | 7 | DE | 0 | subloan |
| 2 | 1 | 4 | AT | 1000 | stock |
| 3 | 0 | 4 | AT | 0 | stock |
| 4 | 1 | 7 | DE | 1000 | subloan |
| 5 | 1 | 7 | DE | 1000 | subloan |
KPIs:
- Number of investments
- mean volume by finished investment process
- Conversion-rate by started investment process
- Expected mean volume by investment process (sum of all investment volume by one started investment process x conversion-rate)
From the above example (per investment process), for the subdivision 'country' Germany (DE), a conversion rate of 66.6% would be obtained with an average volume of 1000 EUR per completed investment process. Thus, DE would have an expected average volume per initiated investment path of 0.666 * 1000 EUR = 666 EUR, while Austria (AT) shows an expected average volume of 0.5 * 1000 EUR = 500 EUR. Consequently, this result would indicate that if marketing expenses were equal in AT & DE, advertising in DE is more efficient than in AT.
Gruppiert by Lead:
| Investor_id | invested | CC | volume_sum |
| 7 | 1 | DE | 2000 |
| 4 | 1 | AT | 1000 |
KPIs:
- Number of investments
- Customer Lifetime Value (CLV) (sum of all investment volumes)
- Conversion-rate (100% if lead = investor)
- Expected Customer Lifetime Value (CLV) (sum of all investment volumes by one lead x conversion-rate)
In the example (this time per lead), both Germany (DE) and Austria (AT) would receive a conversion rate of 100% for the 'country' subdivision, as all leads from the respective countries became investors. Since the variable 'volume_sum' here represents the accumulated volume for a lead, it corresponds to the CLV (Customer Lifetime Value) of the lead. In the context of the subdivision, acquiring leads is more efficient in Germany (1*2000 EUR = 2000 EUR) than in Austria (1*1000 EUR = 1000 EUR), as there is a double expected CLV per targeted lead.
The following charts are structured very similarly according to the same schema.
AGE (by Lead):
The graphic in the bottom right shows the age distribution of platform x over a period y. The largest number of investors is in the age group of 32.
The graphic in the bottom left illustrates the conversion rate divided by age. A clear trend can be observed here, describing a higher probability of a lead converting to an investor as the age of the leads increases. However, it's important to note that while older leads may quickly convert to investors, the total accumulated investments can still be very low, making it difficult to draw meaningful conclusions.
The graphic in the top right reflects the cumulative investment amounts per investor (CLV) and per age group. Similar to the graphic showing conversion rates by age group, an increasing trend in investment amount with age is noticeable here. Hence, the amount invested over the entire lifetime also increases with age.
For marketing purposes, both the probability of a lead becoming an investor and the amount of money the lead will invest over their lifetime play a role. Thus, the conversion rate and the CLV per age group are multiplied, resulting in the KPI 'expected total volume per investor per age group.' In the event that the acquisition costs for an individual are evenly distributed across age, spending marketing budget becomes more lucrative as the person's age increases.
However, since the platform has historically addressed a very large number of young investors, it is now advisable for the platform to focus more on older leads, as they bring significantly higher expected total volume.
STATE (by Lead):
Just as in the charts regarding age, the 'state' subdivision is considered per lead. It becomes evident that platform x has a large number of investors from southern Germany and North Rhine-Westphalia (NRW). In contrast to the conversion rate per state, the total accumulated volume is more informative, with investors from Bavaria (BAY) and Schleswig-Holstein (SH) achieving the highest values. These two states also appear to be the most efficient in terms of the expected total volume of the targeted leads, as indicated by the top left chart.
WEEKDAY (pro Zeichnungsstrecke):
Unlike in the two previous charts, the property 'day of the week' is grouped per subscription path. Here, the lower investments on weekends (weekday 6 & 7) are noticeable, as well as the numerous investments at the beginning of a week. Also, on Monday, the conversion rate is relatively high, approximately 64%. In this example, not only are there few investments on weekends, but those that do occur have a relatively low average volume per completed subscription path (approximately €2300). Considering both aspects, the chart on the top left ultimately shows the relevant information. In this regard, weekends appear to be the least effective days, mainly due to the low willingness to invest high amounts per subscription path. Thanks to the increased conversion rate on Mondays (weekday 1), this day of the week is the most profitable, with an expected volume of €2353 per initiated subscription path, followed by Wednesday and Friday.