Lock-in Effect

What is the lock-in effect?

Lock-in effect (German Lock-in-Effekt or Anbieterbindung) denotes the tie of a customer to a provider that arises because switching involves costs, effort and risks. These switching costs exceed the expected benefit of switching. The customer then stays even with a cheaper or better alternative offer, because switching does not pay off for the customer. Similarly, a tenant stays in a flat as long as the saving from a cheaper rent does not outweigh the move, renovation and effort.

The term comes from industrial economics, the part of economics that studies markets and competition. It is particularly pronounced in business models with recurring revenue, above all in software, platforms and infrastructure services. In funding rounds and company sales, it serves as an argument for stable revenue in the equity story, the case made for growth and earnings prospects. Investors and buyers examine it before signing a contract in due diligence on the basis of customer contracts, usage data and retention metrics. The most important is the retention rate, the share of customers or revenue that is retained.

Types of switching costs with examples

Technical lock-in

Technical switching costs arise when a product is deeply integrated into the customer's system landscape. Interfaces (API) to accounting, merchandise management or production, customised adaptations and automations built on the product would have to be recreated on a switch. Training effort and established workflows also bind, because changing them temporarily costs productivity.

Contractual lock-in

Contractual switching costs result from terms, notice periods, minimum purchase commitments, prepayments or loyalty discounts. They take effect immediately but are limited in time: when the term ends, the decision to switch is open again.

Data-related lock-in

Data-related switching costs arise when the provider holds data that is valuable to the customer and cannot be transferred without loss: histories, configurations, analyses, evidence for audits. This lock-in grows with the duration of use and is strongest when the value lies in what the product derives from the data, such as forecasts from a multi-year history. If the benefit rises with the number of participants, network effects are added: a customer willing to switch would have to take its business partners along.

Significance for customer retention and valuation

Switching costs show up in metrics that investors check directly. These include low attrition (churn rate) and high net revenue retention, that is, revenue from existing customers that stays stable or grows through expansions despite cancellations. A further sign is the ability to raise prices without attrition rising. These variables determine the value of a customer over the entire contractual relationship (LTV) and thus the profitability of customer acquisition. Companies with demonstrably stable customer relationships therefore often achieve higher revenue multiples (revenue multiple, enterprise value divided by revenue). The comparison is with companies that lose more customers at the same revenue and growth.

Investors distinguish by the quality of the lock-in. Lock-in through benefit, that is, through integration into workflows and through data that gains value in the product, is regarded as durable. Lock-in through contract clauses or impeded data export is regarded as fragile, because it ends with the term, damages reputation and can lapse through legal requirements.

Review in due diligence

Investors and buyers distinguish between asserted and measured lock-in. In the pitch deck, a reference to high customer retention is therefore not enough; attrition and net revenue retention are expected as figures. Retention is measured through cohort analyses (cohort analysis), which show what part of the customers and revenue of an acquisition year is still present after several years. Also informative is attrition at the end of the contract term, which allows contractual lock-in to be separated from lock-in through benefit.

In the customer contracts, terms, automatic renewals and extraordinary termination rights are in focus, especially termination rights in the event of a change of control (change of control), that is, a sale of the majority. It is also checked what share of revenue falls on contracts that expire in the next twelve months. Technical due diligence shows how deeply the product is actually integrated into customers' systems and whether data can be exported completely.

Legal limits

Lock-in through benefit is legally unobjectionable; limits exist where it arises through restrictions on the customer. Article 20 of the General Data Protection Regulation (GDPR, German DSGVO) gives data subjects the right to data portability. They can receive the personal data they have provided to a controller in a structured, commonly used and machine-readable format and transmit it to another controller. The right belongs to natural persons, not to businesses as customers.

More important for business customers is the EU Data Act, which has applied since 12 September 2025. It obliges providers of cloud and other data processing services to enable switching providers, including for business customers. Until 12 January 2027, switching charges may at most cover the direct costs of the switch; after that they are abolished entirely.

Pre-formulated contract terms are subject to control of general terms and conditions. In business with consumers, Section 309 No. 9 of the German Civil Code (BGB) limits terms, tacit renewals and notice periods; between businesses, the general standard of unreasonable disadvantage under Section 307 BGB applies. For dominant providers, competition law draws further limits, for example on exclusivity commitments.

Worked example: switching costs and attrition in the lock-in effect

A mid-sized customer uses planning software for EUR 30,000 a year. A competitor offers a comparable solution for EUR 24,000. All figures are freely chosen. The payback period states after how many years the saving has recovered the one-off switching costs.

• Annual saving on switching: EUR 30,000 minus EUR 24,000 = EUR 6,000
• Data migration and cleansing of the history: EUR 18,000
• Rebuilding three interfaces at EUR 6,000 each: EUR 18,000
• Training of 40 users at EUR 300 each: EUR 12,000
• Total switching costs: 18,000 + 18,000 + 12,000 = EUR 48,000
• Payback period: EUR 48,000 / EUR 6,000 = 8 years, without productivity losses from the changeover

Switching pays off only after eight years and therefore generally does not happen. At the provider, the effect shows in the customer base. Suppose it has 200 customers at EUR 30,000 each, that is, EUR 6 million of recurring revenue, and thanks to high switching costs loses 5% of it a year. A comparable provider without such lock-in loses 15%.

• Base after five years without new customers at 5% attrition: EUR 6 million × 0.95 to the power of 5 = around EUR 4.64 million
• Base after five years without new customers at 15% attrition: EUR 6 million × 0.85 to the power of 5 = around EUR 2.66 million
• Lost revenue: around EUR 1.36 million compared with around EUR 3.34 million

The provider with the higher attrition has to replace around EUR 2 million of additional revenue through new customers just to draw level with the other. This customer acquisition costs sales budget before any growth arises. That explains why investors value low attrition more highly.

Distinctions: vendor lock-in, network effects and tax lock-in

• Network effects: rising benefit with the number of participants. They are one possible source of switching costs, but not every lock-in rests on them.
• Vendor lock-in: the dependence of the company itself on suppliers such as cloud providers or third-party platforms. From its point of view it is a risk to costs and freedom of action, which technical due diligence examines separately.
• Retention rate: measures what share of customers or revenue is retained. The lock-in effect is one possible cause of high retention, the retention rate its measurable result.
• Tax lock-in and lock-in in the property market: In public finance, the term denotes that investors hold interests or securities because a sale would trigger tax on the disposal gain. In the property market it means owners who do not sell because new financing would be more expensive than their cheap old loan. Neither meaning has anything to do with customer retention.

Common mistakes

• Lock-in asserted rather than evidenced. The statement “high customer retention” without cohort data and attrition at the end of the term does not convince in the review.
• Term reported as lock-in. Long contract terms stabilise revenue only until they end and do not replace lock-in through benefit.
• No interfaces to neighbouring systems. Without connection to accounting, merchandise management or production, a product does not grow into the customer's workflows, and the most robust form of technical lock-in does not arise in the first place.
• Lock-in through impeded data export. Anyone who makes it harder for customers to get their data released risks, for cloud and other data processing services, a breach of the switching rules of the Data Act. In due diligence, such lock-in counts as a risk, not a strength.
• Change-of-control clauses overlooked. Termination rights of large customers in the event of a sale can remove the lock-in precisely at the time of the transaction.

Frequently asked questions

What are examples of the lock-in effect?

Typical are enterprise software with many interfaces, cloud services with data and workflows grown over years, and platforms on which the customer's business partners also work. For consumers, mobile phone contracts with a minimum term belong here, as do matched devices from one manufacturer and printers that accept only its consumables.

How can the lock-in effect be measured?

Only indirectly. Meaningful are attrition by revenue over several cohorts, attrition at the end of contract terms, the number of active interfaces per customer and the customers' reaction to the last price increase.

Is a strong lock-in effect always good for the valuation?

No. Only lock-in from the benefit of the product has a positive effect. Investors regard lock-in through impeded termination or withheld data as a risk.

Must providers hand over customer data on a switch?

In many cases yes, based on the right to data portability, the switching rules of the Data Act or the contract itself. The scope depends in the individual case on the type of data, the service and the contract.

The Roemer Capital view

In financing and sale documents, Roemer Capital presents customer retention not as a characteristic but as a finding: cohorts over several years, attrition at the end of the term, number of active interfaces, reaction to price adjustments. This compilation is ready in the data room before investors or buyers ask for it.

In a company sale, Roemer Capital reviews the customer contracts early for termination rights on a change of control. If they concern large customers, the topic belongs in the purchase price negotiation and in the plan for how these customers are approached after closing. How the clauses are to be assessed legally is clarified by the client's law firm.