There is a benefit to keeping strategies and tactics simple. This is often reflected in the saying “KISS” — Keep it simple, stupid.

In some circumstances, the investment in complexity is justified by the return, particularly when complexity can be automated. I propose a modification of the KISS acronym to “keep it simple, sometimes.”

Complexity has a high return on investment (ROI) when it comes to the personalisation of customer experiences and relationships. Personalisation of content recommendations, acquisition offers, and retention campaigns supported by analytics that provide propensity scores for subscription likelihood, churn risk, and healthy engagement levels are examples of when complexity is justified.

Operationally, propensity scores are “pushed” to the applications in publishers’ tech stacks that execute these personalised tactics at the appropriate customer touchpoints. This practice is mass personalisation at scale.

Implementation of mass personalisation use cases is often more challenging than the underlying data science, although high-quality data science is very important for success. Personalisation of customer touchpoints needs to work within the capabilities of the tech stack and reflect the strategic objectives of the organisation.

Incorporating A/B testing into the implementation of personalisation to verify the tactics are creating lift and to optimise the messaging is a best practice. Strategic objectives can be reflected in business rules guiding the recommendations provided by the analytics.

Customer data privacy is an important factor for personalisation use cases. Appropriate use of customer data constrains some of the insights and recommendations that can be implemented, but we often advise clients not to let the perfect be the enemy of the good, meaning that some personalisation is better than none.

Subscription pricing is an area where executives often seek simplicity, and there are cases where it is helpful. We have found the ROI on pricing complexity is very high. Here, we describe where simplicity in pricing is helpful and where complexity can dramatically improve results.

Personalised pricing decisions

In a subscription relationship, there are three key pricing decisions during a customer’s lifecycle: acquisition offers, the transition to regular rate after the promotional offer, and annual increases.

For an individual customer, about 80% of pricing decisions are annual increases, since you acquire customers once and keep them for many years. (We use the term “annual increases,” but this decision can also be called a renewal increase if you have subscription terms.) We find the first two pricing decisions are the best for optimising volume and the last one for optimising revenue.

Acquisition offer design includes an introductory price point and an offer length. Industry trends are to have low-price offers that provide access for several months: US$1 for six months is an example. These offers generate significant volume, but subscribers from these offers usually have high churn rates. We have tested hundreds of subscription offers with publishers, and we can share benchmarks for conversion rates, churn rates, and lifetime value.

Simplicity works best with acquisition offers among the pricing decisions. Offers that are easy to communicate, understand, and remember perform well. Offers can be targeted to consumers by channel or for readers where you have data to support propensity models. However, in most cases, the ROI from targeted pricing at this point is not as great as later in the subscriber lifecycle.

Transitioning a subscriber from the acquisition offer to the regular rate is a challenging step in a subscription relationship. Customer engagement is an important predictor of retention through this phase, and many publishers are testing proactive retention offers for high-churn-risk customers reaching the end of their promotional offers.

Many countries require disclosure of the price the customer will pay after the promotion offer. We find that the “next rate” does not affect conversions at the point of purchase, but higher rates do cause higher churn upon transition.

It is OK to move a customer to a lower rate than what was stated at acquisition. Targeting customers for lower transition offers is a challenging business case since the required retention lift to offset the lower average revenue per unit (ARPU) is a high bar to reach, but complexity in the form of targeting does have a positive ROI.

Dynamic pricing of annual increases is where additional complexity has a significant ROI. Segmenting your customers by price elasticity can identify those subscribers most likely to stop after a price increase.

The 80/20 rule — where 80% of your price stops are coming from 20% of your customers — is an accurate description of the opportunity for optimisation. Avoiding or minimising price increases to high price elasticity customer segments can significantly reduce churn and increase the net revenue yield from pricing changes. Giving higher increases to those customers that place a high value on the product and who can afford higher prices offsets the lower yield for high-risk customers.

We find that digital subscribers have similar price elasticity to print customers, and increasing ARPU from digital subscribers is necessary for sustainable digital business models.

How does our data protection officer look at this?

Implementing dynamic pricing strategies involves the collection and analysis of customer data, which may include browsing history, purchase behaviour, and demographic information. It’s important to emphasise that dynamic pricing strategies are permissible under relevant privacy laws, as long as they align with the data protection requirements set forth by those laws.

As a consequence, to harness the benefits of dynamic pricing while safeguarding customer trust and privacy rights, it is important to prioritise transparency and data protection in these practices.

Keep it simple, sometimes

Dynamic pricing can be implemented in a relatively simple pricing framework. A few price points are sufficient to realise most of the gains, and we can advise you on the tradeoff between more price points and higher yield.

We agree with the principle that simplicity is best in most cases. However, the increased sophistication of modeling approaches and the capabilities of technology tools provides opportunities for publishers to use complex strategies and tactics effectively.

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