Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Accelerate Your Offer Personalization Journey with Test and Learn Processes

One of the greatest misconceptions about the personalization journey is that it’s a simple box to check on a list of features for martech software, and that it’s static. In fact, real personalization is the ability to use insights about the customer to improve the customer experience and to adapt to each customer, over time.

Your customer base will continue to evolve and change throughout the years they are loyal to your brand, so what is personalized and engaging for them today might not work in one year, and it definitely won’t work in three years. To build personalization into an organization’s capabilities, the technologies in place need to constantly test, learn and optimize what customers need, so the next experience or offer is tailored for them.

If continuous personalized offers and experiences are something your brand is ready to tackle, you’re starting the journey at the right time.  Research from BCG shows that redirecting 25% of mass promotion spending to personalized offers would increase return on investment (ROI) by 200%, leading to a top-line growth opportunity of more than $70 billion annually.

Yes, that’s $70 billion, with a B.

For example, according to BCG a “large convenience and drug chain in North America scaled a branded-offer capability that allowed vendors to fund personalized offers at scale. During the pandemic, this enabled a significant shift away from mass promotional funding… the capability generated $100 million in net incremental revenue and increased the number of customers interacting with personalized offers by 50%.”

That’s a huge gain for the company, especially during a period of time when consumer shopping habits were rapidly shifting and 75% of shoppers tried a new brand due to the proliferation of digital shopping options.

Clearly it’s time for brands to get started on this journey toward personalized offers. The technology exists to implement, and first-mover brands that tackle this challenge now are going to achieve massive revenue gains, while those that lag behind are likely to be put out of business by their competitors.

Related Posts
1 of 3,722

I recognize that it’s not a simple, overnight task to shift from mass to personalized offers. Because it’s not just about shifting budget dollars, it’s about creating an entire new strategy around personalized promotions, and accepting that there will be possible revenue impacts as the company shifts away from mass promotions. However, the long-term business impact of these strategic shifts can be incredible, and the short-term impacts can be improved with a test and learn model.

Creating loyalty in our modern world requires personalization processes that are data-driven and continuous, because what is unique to a customer today will change over time. To create a lifetime of value and engagement, brands need to keep testing ideas and learning about their customers. Machine learning technology can automate that learning as customers evolve their purchasing habits, both individually and as a group, and provide actionable data to brands that will create deeper engagements. Instead of constantly tweaking mass campaigns, trying to optimize one program for millions of customers, human power can be dedicated to creating the right strategies for revenue growth and machine learning capabilities will constantly test-and-learn to ensure campaigns are continuously optimized.

Mass discounts have long been the leading strategy for driving revenue from existing customers, because personalization at scale was simply impossible. And because there is very limited to no testing with mass offers, they have become a predictable tactic that teams run, over and over again, because there isn’t enough data to change the strategy. Relying on mass offers makes personalization so much harder, because there is no real learning involved about a customer or audience, so marketers continue to operate on a hypothesis, rather than having continuous data-driven insights to take action upon.

But that is no longer the case. Brands that are ready to take the leap and begin transitioning to personalized offers have a number of off-the-shelf technology options available that will automate much of the effort. No surprise that 71% of brands plan to invest or increase investment in offer optimization technology in the next 12 months.

Top Martech News: Snap Launches Multi-format Delivery to Improve Ad-buying Experience

Moving your brand away from the traditional mass discount or standard end of year sales communications takes time – you’ll need to re-train your internal team on how to measure the impact of loyalty offers AND you’ll need to re-train your customer base not to wait until they get a coupon to shop. But there is a greater risk in not making the shift now, because innovative brands will start to steal share of wallet from those that are not creating personalized offers to engage their base.

Ready to get started? BCG suggests focusing on the customer experience, technology, and operating models first, and identifying areas where you can secure some quick wins. Good luck!

[To share your insights with us, please write to sghosh@martechseries.com]

Comments are closed.