Finding the right privacy-centric solutions that continue to drive performance can be difficult, especially with many platforms offering assistance. The restrictions on data contribute to marketers having less control over targeting users effectively. The over-saturation of marketing emails and texts to consumers and the continuous decline in consumer trust makes personalization a much harder task for marketers. New regulations and tracking barriers made by tech companies are obstructing the effectiveness of personalization, especially advanced forms of personalization such as hyper-personalization as they require users to disclose personal information, such as purchase and browser history, demographics and preferences.
Personalised marketing in a privacy-centric climate
The latest privacy changes to our marketing realm will affect how e-marketers target their customers. The GDPR isn’t preventing marketers from collecting data, these new policies are in place to protect users who do not want their information monitored without their consent. Marketers should focus on using 1st Party Data and machine learning to release personalised content and effectively target the right consumer. Machine learning and algorithms play a huge role in how we target our customers. Instead of using personal data, marketers should process aggregated data. These regulations mean that personal data should not be used to measure or make decisions about a particular person without permission.
Artificial intelligence plays a major role in removing privacy-based obstructions by compensating for the lack of data by making predictions that allow businesses to personalise their strategy. These algorithms determine which customers are more likely to buy and when. Predictive algorithms track the user’s information and then provides insights and suggestions.
The first step in approaching a privacy-focused personalization strategy is by understanding your goals and implementing a strategy that uses personalization as a method of hitting that goal. To achieve greater results and obtain more data, implementing an omnichannel strategy will also be beneficial as you will be able to see how your targeted audiences respond to different channels, using your own channels to learn what is working well and what isn’t.
One of the most effective yet simple tools to tackle this privacy obstruction is ‘Consent mode’, a banner or message asking the user if they accept cookies and are not opposed to sharing useful information that contributes to receiving relevant adverts. This banner displays your brand’s transparency to your consumer and eradicates the idea that data is used maliciously but rather for the user’s good. Those users who accept the cookies will increase the data you have stored and will be useful for optimising your e-commerce strategy.
Understanding your customer’s lifecycle and how your marketing efforts will affect their journey will also benefit your strategy. Do not bombard them with messaging and force them to turn away before completing any CTA or even dropping an email. This can restrict your chances of gaining the user’s insight. Algorithms work out the best placements for your messaging and the most effective structure that compliments their journey. Improving the onboarding experience for new customers and providing them with a benefit, such as a discount, can sway them into providing contact information which can be later used to send personalised messages.
What personalised adverts are, what they achieve and how they use data
Personalised adverts ( also known as interest targeting) is a marketing tool that places a particular ad before a user with a specific interest, depending on what sites and apps they have previously visited. Personalised ads improve the advertising relevance for users and increase ROI for advertisers by displaying the right ad in front of the right user increases the chances of conversion. Personalised adverts have played a major role in eCommerce advancement and have helped many businesses drive performance and increase their ROI throughout the pandemic.
Data enables retailers and eCommerce businesses to establish the most effective strategies to target their customers. The insights provided by Machine learning-based programs, such as Guass Smart Advertising, help brands establish any trends and re-occurring patterns made by their page visitors. This will help map out the most effective promotional activity to the users who are most likely to engage, which additional or add-on products they are likely to purchase and the best time for the specific messaging to be shown.
Personalised ads enhance the customer’s experience. Similarly to a sales assistant recommending products in-store, personalised messaging assists in recommending products to the right users. These ads can be placed in particular touchpoints of a user’s journey, stimulating them to finalise a purchase. Another benefit of incorporating personalised messaging into a user’s journey is determining where they are being halted from completing their purchase and building a bridge over it.
This strategy contributes to driving performance at scale by targeting a specific audience with a specific message, rather than spending money targeting all the users with a message that supposedly applies to all but will only be effective on a small amount.
Balancing automation and control to drive results
As much as we can depend on machine learning to provide insights, we cannot simply depend on these tools. Marketers must also control the content and strategies that are decided after analysing the data. An important factor that can be easily forgotten about is branding and building strategies that correlate with the objectives and values of your brand. Alongside driving sales, you want your brand to provide a unique experience that keeps your customers coming back. To do this, you must infuse your brand message into your strategies and incorporate it within your e-Commerce platform.
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