One potential measure to limit the scale of user data held by market incumbents is to restrict the retention period of raw data, such as search queries entered by users or location data. According to Chiou and Tucker (2017), even with a shortened retention period, the learning capacity of platforms inferred from data did not significantly diminish. By applying incremental learning techniques, where new models are trained based on existing models and continuously refined with new data, the platform's learning capacity could remain largely unaffected, even with a reduced data retention period. However, if a significant amount of raw data is quickly deleted, there may be some impact on the flexibility and efficiency of the learning models. This is suggested by the fact that, despite Chiou and Tucker's (2017) findings, many analyzed platforms extended their data retention periods after initially shortening them, citing the need to enhance personalized services. On the other hand, if data retention periods are shortened, market incumbents with large user bases may still gather significant amounts of data within the limited retention period, while market entrants with smaller user bases may struggle to collect enough data for meaningful analysis, potentially reinforcing the competitive advantage of incumbents. Additionally, a shorter data retention period could limit the amount of user data shared by incumbents with new market entrants. This would likely restrict the ability of entrants to narrow the gap in insights derived from data compared to incumbents.

Another potential solution to ensure competition in the digital platform market is to limit the combination of user data obtained from various services by dominant platforms. This is aimed at preventing the so-called "domino effect" in the digital platform market. To achieve this, data should be stored in separate databases or data silos within the service from which it was originally collected. Under such measures, both incumbents and new entrants would have the same incentives to enter adjacent markets without any inherent competitive advantage. However, these data silos could hinder the realization of economies of scope that data provides and limit the efficiency that data combination could bring. For example, integrating and interoperating data between email, calendar, and map services could allow users to create appointments from received emails and easily derive travel routes and estimated arrival times from map services. In other cases, combining data from various services may not create synergy but could harm consumers. For instance, tracking users across different services for targeted advertising purposes could violate their privacy.

Restricting the business activities of digital platforms is a strong form of intervention that fundamentally prevents platforms from collecting and combining more user data. In a broader sense, ordering the separation of vertically or horizontally integrated business groups could also be considered a form of business activity restriction. In the past, restrictions or separations were implemented in several network industries, such as energy, railroads, banking, and broadcasting. However, not all of these interventions were effective, and more recently, such measures have not been commonly taken by competition authorities, either ex post or ex ante. Nonetheless, there have been continued calls for business activity restrictions in the context of digital platforms. For instance, in 2019, India banned foreign e-commerce platforms from directly selling to consumers, and in 2021, a bill was introduced in the U.S. to prohibit online platforms from using their platforms to sell their own products or services, or from owning or controlling other businesses that use their platforms. Restricting business activities would naturally prevent data combination, resolving issues related to monitoring and enforcing data combination policies. Additionally, it is argued that such restrictions could promote diversity and contribute to non-economic policy goals, such as enhancing system resilience. However, there are also downsides to business activity restrictions. First, when restricting business activities or separating certain lines of business, there are several practical challenges. It is often difficult to clearly define the boundaries between different digital markets or services. Furthermore, business activity restrictions, like data combination restrictions, prevent the positive spillover effects that information generated in one market or service could have on another market. This is one of the main reasons why digital platforms actively expand into adjacent markets. Moreover, as highlighted in existing literature on business separation, splitting or reducing business activities weakens the efficiencies derived from economies of scale and scope. Specifically, the separation of vertically integrated businesses can lead to the problem of double marginalization, creating additional inefficiencies. Therefore, if business activity restrictions are implemented, they should aim to minimize these inefficiencies.