In today’s uber-connected world, omnichannel marketing is one of the most effective ways of capturing consumers’ attention.
With competition skyrocketing and digital transformation supercharging customer expectations, 90% of people now demand seamless, consistent interactions across all digital channels. As a result, businesses that use some kind of omnichannel strategy achieve 91% greater year-over-year customer retention rates than business that don’t.
But customer expectations are increasing at a pace that’s extremely difficult to match: Despite how critical an omnichannel strategy is to success, over half (55%) of companies report having no such strategy in place. And without one, they risk losing customers and leaking revenue.
What’s holding companies back from implementing omnichannel marketing strategies – and how can they overcome these challenges?
Taking measures: The data analytics challenge of omnichannel marketing
Measuring results and effectively attributing data has been one of marketers’ biggest challenges over the last decade. And, when it comes to omnichannel marketing, this challenge is even more daunting. Omnichannel strategies require very precise measurement of campaign efforts across all online touchpoints as customers are driven down the funnel. That all adds up to a huge amount of data for teams to keep track of, analyse and draw conclusions from.
For example, say you’re an online retailer and you’ve got dozens of campaigns running across multiple digital channels. In order for your omnichannel strategy to be effective, you need to know how your customers are interacting with these campaigns, what stage of the funnel they’re at and how effective each of these campaigns are. That’s an awful lot of data, coming from a lot of different places. Combing through all that data to analyse and understand it is going to take an enormous amount of time, money and manpower. And we’re only human, so we’re likely to make mistakes when doing this kind of data analytics manually and overlook things we simply can’t see in the metrics.
As a result, 64% of marketers who don’t have an omnichannel strategy say it is because of a lack of resources and investment. The sheer amount of data analysis needed for omnichannel marketing to work is one of the key reasons why it’s a strategy that’s so hard to adopt. Without proper data attribution, marketers cannot effectively analyse and make data-driven decisions using their metrics.
Luckily, when it comes to supercharging omnichannel marketing, there’s one technology that makes this data analysis easy: AI KPI analysis.
AI KPI analysis for supercharging and scaling omnichannel experiences
When it comes to analysing data at scale, humans simply aren’t up for the job. Even the most data literate among us make mistakes, and when there’s hundreds of metrics and dimensions to understand, it simply takes too much time.
But AI (like the one that powers our tool, Millimetric) is exceptional at analysing data at scale. AI algorithms can be trained to scan through all your data, 24/7, for any unusual patterns, trends or anomalies that occur, and alert you to them immediately. Because AI is so much more efficient at data analysis, it can detect patterns invisible to the human eye, so can identify things you would miss if you were to analyse the data manually. Because it’s doing this constantly, it can pick up on issues in your data in real time. This allows you to tweak your campaigns as they’re running, rather than waiting to get the results.
And AI KPI analysis can do all this number crunching in seconds, saving you huge amounts of time, money and manpower.
Alternative ways AI can improve omnichannel marketing
Of course, automated KPI analysis is just one of the ways that AI can improve the omnichannel marketing experience. There are some other brilliant ways that harnessing the technology to supercharge your omnichannel strategy, including:
- Data collection and cleaning
- Customer service AI and chatbots
- Tools for using inventory at its most profitable price point
- Dynamic adjustments