Have you ever received personalised recommendations from your favourite brand? Has this lead to you buying those products? Or thinking they were actually good recommendations?

Once you’ve signed up to receive newsletters from your favourite companies, some places think it’s okay to bombard you with emails about information that isn’t relevant to you, some send the occasion email with products that are ‘personal’ to you as a customer. But are they ever actually personal to you? Or is the same email sent to millions of other customers? ‘A survey about marketing messages conducted by Lyrics revealed that 63% of consumers report that they now receive so many messages that use their name that it no longer has any impact’ (Davey, 2014).

Doesn’t it make you wonder how much your favourite brand knows about you? Where are they getting this information from? This blogs looks at the risk/problems for companies who send personalised product recommendations to their customers via email or on their website as the consumer is about to purchase something from them.

SO… WHAT ARE THE RISKS?

Most negativity about personalised recommendations, come from the customer side and this is either due to the products they have been recommended are something they would never normally buy and doesn’t suit you at all or it’s too specific and it’s a combination of products that the consumer has already purchased.

1 | Privacy Issues

Some consumers can see it as being invasive when companies use a system that recommends products based ‘on the demographics of the consumer, or on an analysis of the past buying behaviour of the consumer as a prediction for future buying behaviour’ (Zhang et al, 2015). Therefore, running the risk of invading a person’s privacy and this could have a damaging impact on their loyalty to the company.

2 | The Filter Bubble

A filter bubble is a result of a personalised search in which a ‘website algorithm selectively guesses what information a user would like to see based on information about the user’ (Bozdag & Hoven, 2015). This is a problem because it means that customers will only be seeing products that are based on what they have purchased in the past and leaving out potentially new products that could equally be as beneficial to the consumer.

Watch the video below for full information about the filter bubble.

An example of this, is that within The Body Shop, they have a variety of different ranges of products which use different ingredients and are for different skin types, skin problems etc. However, if you buy from one specific brand range, you only see products recommended within that brand range.

Therefore, this is limiting customers to only buying within that specific range rather than them being recommended products from different ranges within The Body Shop.

3 | Accurate Data

 There is nothing worse than getting recommended products that have no interest in you as a consumer and it makes you wonder how accurate the data the company is using. Is there any way you can trust their recommendations in the future after they’ve failed to recommend you anything within your interests?

Sandra McDill, managing partner at iProspect, stated “mistakes often happen when assumptions are made based on data that is incorrect or incomplete leading to a bad personalisation experiences”. Therefore, making sure that the company has a system in place that checks the accuracy of their database before making personalised recommendations is vital.

Netflix had a problem with their recommendation system when if more than one person had access to the account and each had different tastes in movies, the algorithm would be less likely to select things that either liked. However, this was fixed when Netflix rolled out the ability to add multiply profiles to one Netflix account, allowing Netflix to recommend movies and TV series to each individual profile rather than as a whole to the account.

FINAL THOUGHTS…

There needs to be systems in place to make sure that the customers feel comfortable with what their details and browsing/purchasing history is being used for. If the recommendations become to personal, this could put the customer off from using that specific company to purchase. However, it is the companies’ responsibility to make sure that although they need to filter the information for the customers, that it’s not too filtered and that they aren’t missing out on products that could be beneficial to them, even if it may not be within their interests.

It’s always good to try something new every now and again!

References:

Davey, N. (2014). Personalised marketing: the wrongs, the rights and the recommendations. Available: http://www.mycustomer.com/marketing/strategy/personalised-marketing-the-wrongs-the-rights-and-the-recommendations. Last accessed 28th Feb 2017.

Fidura, S. (2015). Why email marketing is still the leader of the pack.Available: http://www.telegraph.co.uk/sponsored/business/business-reporter/11127852/email-marketing-platform.html. Last accessed 28th Feb 2017.

Zhang, Y., Qi, J., Shu, H. & Cao, J. (2007). Personalised product recommendation based on customer value hierarchy, IEEE, , pp. 3250.