Hyper-personalisation is a consumer expectation; why are so few companies doing it well?

The sub-optimal use of consumer data is a constant bugbear to many industry experts and consumers alike.

Most companies have a myriad of data sources, across a wide spectrum of both loyalty and non-loyalty customers, but the sad reality is that this data rarely translates into proper insights, which drive actionable consumer facing campaigns that move the needle.

There are 3 main reasons for this.

 

Lack of know-how

The mindset of many companies is still to send a one size fits all email or SMS and hope for the best. A lot of the time it’s because there simply isn’t enough loyalty or customer centric expertise within the business, so there is often a lack of understanding of what is best practice and the long-term impact it could have.

At best, this is highly ineffective because of the sheer diversity of the customer base and at worst, it’s gross negligence in delivering anything of actual value. The lack of value and personalisation will cause the customer to eventually disengage and it’s no surprise that unsubscribe rates are broadly at an all-time high.

A good example is a recent SMS I received from Volkswagen, offering me a $500 voucher to buy a demo car (which in itself is fine). Problem is, I bought a brand-new car from that dealership exactly 12 months ago. Volkswagen have the date of purchase, and I’m positive they know that most people don’t buy a new car every year.

A different approach might be to leverage a referral mechanic and ask me to pass the $500 discount on to family and friends. Should anyone take it up, I’d also get $500 off my next car purchase, whenever that might be. That would not only be a lot more relevant to me, it would also broaden their reach significantly at no additional cost to them.

 

Highly manual processes

Many companies I’ve worked for, or consulted to, typically have at least 6-7 different data sources that they use to derive analytics to subsequently report to senior management.

These usually include some or all of:

  • A financial source (i.e. a ledger)
  • A payment gateway or fraud reporting
  • A customer service team (i.e. NPS)
  • A CRM platform (i.e. from sales efforts, loyalty program, or both)
  • A BI platform (i.e. Tableau)
  • Google analytics (i.e. website)
  • SQL (i.e. multiple relational databases that store information on financial transactions, sales transactions, customer details, etc)

With that amount of information, it can be incredibly difficult to not only get an accurate picture at a holistic level, but also to establish a robust process that captures the right data, which can then be used to better personalise offers and communications.

 

Competing priorities

Most larger companies have analysts, whose role it is to look at data and derive some type of actionable insight. Resourcing remains a key issue within most companies. In all but the largest companies which have dedicated loyalty analysts (such as the frequent flyer and supermarket programs) priorities are constantly diverted from data analysis that could be used to improve customer personalisation to other areas of the business.

However, having a large analytics team still does not guarantee personalisation. I continue to be sent emails from Woolworths Rewards which are completely irrelevant – a week ago, I received a 3x points earn offer on Pet Essentials, a product category which I have never bought from Woolworths.

Research continues to show that shoppers are becoming impatient with irrelevant offers. In today’s dynamic and competitive environment – as highlighted in Aldi’s recent television advertisement – the earn and redeem model by itself is simply not enough anymore.

This shift in behaviour means it’s critical for brands to focus on the activities surrounding the buying experience, as much as the buying itself. A company’s ability to form a relationship with its customers is what maintains its relevance and customer engagement.

 

As part of past consulting projects, we’ve completed detailed analysis for a number of our clients including Vintage Cellars, Liquorland, First Choice Liquor, My House, Sportsbet, Sumo Salad and HOYTS. The purpose was to understand core customer data and use that data in a more effective way, informing future loyalty, digital & marketing strategies.

If you’re looking for help with data analytics, to better inform your decisioning in a highly competitive and saturated market, feel free to reach out. We are always happy to talk.

 

Max Savransky is Loyalty Director of Loyalty & Reward Co, a leading loyalty consulting firm based in Sydney. He has 10 years’ experience within the loyalty industry including roles at Mastercard Loyalty (Pinpoint), Silverneedle (Next & Sage Hotels) and Pureprofile. As Loyalty & CRM Manager at HOYTS, he launched the highly successful partnership with Qantas Frequent Flyer, including a world-first Qantas Points in-store redemption proposition. He is an active cryptocurrency trader.

Max regularly contributes to www.blockchainloyalty.io, a global resource centre for everything blockchain loyalty.

 

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