How Can Clean Data Use Improve Telemarketing Results?

In some ways, the business of life science telemarketing has changed very little, as the methods of contacting potential customers remain the same. However, there are now better opportunities than ever before to use clean data to improve targeting in campaigns.

This distinction between the ‘how’ and the ‘who’ is important. On the one hand, when the right people are reached, campaigns using telephone contacts or emails can be extremely useful in generating leads, following them up and leading them along the buyer journey.

However, the process can be far more effective and efficient if the right prospects are identified before the first contact is made.

Why Are Some Cold-Callers More Successful Than Others?

On its own, cold-calling appears to have experienced diminishing returns in recent years. Research by Business telecoms firm Call Hippo, complemented by other research, has indicated a significant fall in responses to such calls around the world.

The study was based on 72,000 B2B calls carried out between more than 3,000 businesses in over 20 countries, over a 90-week period ending in 2025. The key findings were:

•       On average, only 2.23 per cent of those called booked a meeting in response
•       This figure was down from 4.82 per cent in 2024
•       Conversely, teams using ‘clean data’ and following up their calls had a 6.7 per cent success rate.

The point about clean data indicates that correctly identifying targets is an important factor in making progress. Follow-ups are also important, but these are only worth doing if the original lead turns out to be a good one.

Clean data is distinguished from dirty data by not constituting inaccurate, outdated or duplicated data. Having dirty data when making calls can lead to the following issues:

•       The wrong person or number being called
•       Someone who has already declined being contacted again
•       Poor data segmentation means prospects are not placed in the correct categories
•       Inconsistencies in tagging mean many prospects are recontacted because they are listed as promising when this was not warranted by their original response

Why Are Marketers Using Clean Data At An Advantage?

As Marketer Magazine noted recently, the consequences of poor data include misdirected personalisation, wasted marketing spending and irrelevant audience targeting. This will apply to all marketing, but telemarketing will be affected, as it is using the same poor data.

The article stated that the key approach is to understand that removing poor data and replacing it with ‘clean’ data is not just a matter of tidying up databases, but seeing clean data as an essential piece of marketing “infrastructure”.

Such an approach means that priority is given to auditing data ahead of campaigns, rather than doing so retrospectively following disappointing results.

The benefits include better segmentation of target audiences, more accuracy and better results when data is fed into predictive AI models.

In emphasising these issues and their importance, the article highlighted steps that can be taken ahead of campaigns to ensure the data is cleaner:

•       Ensuring that audits are regular and that campaigns never start with information that was not checked recently
•       Checking for consistency of behavioural data logging across sources to avoid conflicting and misleading information that could lead to contacts being chased with little prospect of success
•       Establishing ownership in organisations for data quality, so that there is somebody who has direct responsibility for ensuring it is good and up-to-date

How Does Clean Data Help You Target And Segment Prospects?

A useful way to consider the implications of this is to think of core marketing concepts such as the buyer persona.

In this instance, the buyer of life science-related goods and services will do this on a B2B basis, hold a particular position in a company and their firm will be in a particular sector that will make use of such products.

The primary requirement, therefore, is to ensure a target fits these criteria for first contact. However, it also means that their response to any initial contact is correctly recorded in order to guide future communications.

For example, a contact may respond with a resounding no, in which case they should be removed from future contact lists, which highlights the importance of avoiding duplication.

By contrast, if they show an interest, they may be classed as a ‘qualified lead’. But this may also be segmented between those who would be keen to hear back soon and those who state that they have no present need for what is on offer, but may have in the future.

Clean data is not a ‘nice-to-have’, but an essential element of a successful telemarketing campaign. The evidence is clear that those who use the right information in an effective way enjoy much better results.