Publishers often ask: “How will our marketing spend on the TrendMD platform affect our readership over time?”
TrendMD’s simple pricing model ensures that for every US $1 spent with TrendMD, a publisher will receive at least one new visitor from outside their network.
We measured TrendMD’s effects on article views per month across 12 journals, each with different marketing spending. The trend was clear: more spending = more readership.
TrendMD's Effect on Article Views Over Time
Once these new visitors arrive, a substantial fraction of them will explore and discover more articles on the publisher’s site and can be expected to return later. This is illustrated in the graph below, which shows how the traffic increases over time, excluding usage by visitors sent via the TrendMD network (which we refer to as the ‘organic’ views). Notably, the higher the marketing spend, the greater the rise in ‘organic’ article views.
Impact of Marketing Spend on Visitor Retention
However, that is not the only part of the story.The graph below shows data for 12 publishers on the TrendMD network, ranked according to their monthly marketing spend. It also looks at the fraction of users who return to the site each month following the first month of a 5-month trial period.
Larger marketing spends deliver a higher percentage of visitor retention, and we can use this to build a quantitative model for the effect of different marketing budgets on overall usage levels.
Modeling the Effect of Different Marketing Budgets
To create and visualize this model, we consider a ‘standard website’ with 100,000 article page views per month as a usage level at the beginning of the period.
By plugging in the mean retention values seen at different levels of monthly marketing spending, we see the following predicted results in the boost in readership for this ‘standard website’ at different levels of monthly marketing spend.
Key Results from TrendMD’s Marketing Model
The above graph shows two especially notable results:
- In all cases, the aggregate return rate of acquired visitors increases over time, demonstrating the longer-term pay-off from sustained marketing through the TrendMD channel.
- Higher marketing spending leads to a proportionately lower cost for each additional access. i.e. increasing returns. This follows from the model because there is a positive correlation between the number of additional visitors acquired (driven by the marketing budget) and the percentage retention of these new visitors. For example, for publishers spending $1K-$2K/month, we recorded the percentage retention at over 20%, but at lower spends ($100/month), the percentage retention was also substantially lower (~8-10%).
TrendMD also offers volume discounts; higher monthly spending = lower cost per visitor. This yields even higher percent increases in readership for journals on the TrendMD platform. For example, $2,000 per month yields >20% increase in readership.
The Mechanism Behind Increasing Returns
Is there a plausible mechanism to explain why such ‘increasing returns’ are seen?
Certainly, let's look at how TrendMD uses collaborative filtering to target readers. Increased spend will provide additional data for collaborative filtering and build a clearer picture of which readers will find which articles of interest across the network.
For example, Reader A has a particular reading history. A TrendMD link appearing on Publisher Y sends Reader A to Publisher X’s site. Reader A later returns to Publisher X’s site (within 30 days) and views other articles. TrendMD’s collaborative filtering can build a picture of which articles are likely to be of most interest to readers with similar histories to Reader A and can target across the network on that basis, preferentially showing Publisher X content to readers with reading histories similar to that of Reader A.
The higher the marketing spend on TrendMD, the more incoming visitor data there is to drive the collaborative filtering algorithm, and the more effectively TrendMD can optimize the placement of external links to bring better-targeted visitors to whom the site is of more interest, so who are proportionately more likely to return.
For lower marketing spending, the smaller number of external visitors means it takes TrendMD longer to optimize recommendations through collaborative filtering. So, at any given time, the incoming visitors will not be quite as well-targeted and ‘sticky’ as in the higher-spend scenario.
Conclusion
A key message from these data is that a publisher’s spending on marketing via TrendMD is an investment that pays off increasingly over time and helps build a sustained increase in audience. The more traffic that comes through the TrendMD channel, the more optimized the channel becomes for delivering precisely the right target audience — users who will continue to repeat visitors to the publishers’ content.
