Why AI-Driven Campaign Message Testing Methods Are Far Superior To Traditional Methods 

by Kristen White Blogger Marketing messages continuously evolve. It’s almost like a “game” between marketing experts and consumers. But, for far too long, the game has been one-sided. Marketers have kept communicating messages to target their audience that they ‘think’ will be the most effective. However, there’s not enough consideration for how consumers will respond to these marketing messages in this equation. Marketers either expect them to sink or swim.

A 2020 survey involving some of the nation’s leading CMOs revealed that large-scale businesses are now spending 11.3% of their entire firms’ budgets on marketing. What happens to the firms who can’t devote such amounts to marketing, let alone marketing research?

Does Spending on Market Research Guarantee Returns for Smaller Businesses?

There are basically five types of ‘traditional’ testing methods for analyzing the efficiency of marketing messages –

- Post-campaign evaluation.
- A/B testing.
- Pre-testing of advertising by surveying a small group of people (on and offline).
- Screening of different concepts and marketing strategies.
- Gaining insights from the market for developing advertisements or marketing messages.

These methods of marketing research are all qualitative. Qualitative testing of marketing messages usually gears towards repeat buyers or loyal customers. Loyal customers don’t require much convincing. They accept the marketing messages and concepts that’ve been reflected in the past campaigns. Essentially, they give businesses a false sense of assurance that they don’t need to change their marketing messages.

That’s why many small businesses fail to attract infrequent or non-buyers because they don’t effectively change their marketing messages of strategies to expand their customer base. There’s a major problem with determining the efficiency of a marketing message using only these qualitative measures. Producing creative marketing messages is very expensive. Not many businesses can afford to make mistakes.

Data-Based Approaches

Thankfully, there are new ways of testing marketing messages that are far more effective and results-oriented. These methods are purely data-driven. An advanced message design and development company can help businesses formulate hundreds or even thousands of marketing messages before they even spend a dime on their advertising campaigns. Sounds too good to be true? That’s what AI-powered (Artificial Intelligence) testing methods are – they’re smart message testing methods that are data-driven.

Why Using Artificial Intelligence Tools for Testing Marketing Messages Works

AI-powered message testing platforms are powered by customer behavior data. Big companies like Spotify, Netflix, Amazon, etc., have already started investing heavily in marketing analytics to collect larger amounts of data and drop-feed them to these machines to get more detailed and precise marketing solutions. By 2022, spending on marketing analytics is predicted to increase by over 200%. These tools can -

- Improve the efficiency of marketing messages in terms of the personal impact they create on individual consumers.

- Message testing using AI-powered tools can be a thousand times more effective and produce highly data-based results compared to manual testing methods like A/B testing.

- As these software-based tests are repeated, the source code and the data sets are modified and improved. Over time, with these advanced campaign message testing methods, the quality of marketing messages keeps improving, even without the use of large sample sizes.

- These tools can rank good, bad, and the best messages, which enables marketers to make confident messaging decisions.

The right marketing messages can dramatically improve the effectiveness of a promotional campaign. Small businesses must avoid “guessing games” and spend their money on these data-based methods.

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Created on Jan 11th 2021 04:14. Viewed 353 times.

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