Amplitude recently hosted webinar featuring global research and advisory firm Forrester to discuss how companies can leverage Digital Intelligence Platforms to drive growth. Guest speaker Brandon Purcell, VP, Principal Analyst, Forrester, joined Amplitude's Product Evangelist Adam Greco.
- Why digital intelligence matters and the impact understanding digital behavior can have on your organization
- Advancing maturity in digital intelligence
- The changing digital intelligence stack
- Emerging trends you need to know
- Opportunities afforded by AI, and more
The conversation was followed by a Q&A session where Brandon and Adam addressed queries from the audience about digital intelligence.
Why digital intelligence matters
When your customer's interactions with you mostly happen in a digital environment, digital intelligence is how you listen to them.
Brandon explained that the acceleration of digital adoption during the pandemic advanced the need to understand customers’ digital interactions with you. Traditionally, businesses have relied in part on face-to-face customer interactions to understand their needs. Today, organizations must “listen” by analyzing data. Adam added that this is even true for brick-and-mortar stores since a significant portion of their business is now digital.
According to Forrester’s Future Fit Survey, 2022, almost 85% of companies surveyed are investing or planning to invest in digital intelligence in some way. Brandon suggested that the 14-15% who don't invest in digital intelligence will decrease over time as more and more companies realize its importance.
Adam proposed that some “old school” companies might be avoiding digitization and will probably “pay a hefty price” as a result. The two agreed companies that don't invest in Digital Intelligence Platforms will likely be displaced. “They're exposing themselves to potential disruption” by companies that do embrace digital optimization, explained Brandon.
Advancing maturity in digital intelligence
Companies that aren't mature in terms of digital intelligence simply collect and report on data. Mature companies use that data to adapt their business and optimize experiences for their customers.
Brandon explained that a critical component of digital intelligence is a continuous cycle of customer experience improvement. The cycle starts with collecting and managing data. Unless you can analyze the data meaningfully, he emphasizes, “it's useless.” The second part of the cycle is the interpretation: analyzing data to discover signals, patterns, and anomalies.
The next phase is action: optimizing the customer experience based on the insights you discovered. The final phase involves measuring the efficacy of your actions by monitoring them over time.
Adam laid out how those phases map onto the Amplitude platform. Amplitude allows users to:
- See: Listen to customers by collecting data.
- Predict: Conduct analyses to anticipate how customers will behave.
- Adapt: Improve and optimize the customer experience based on data-backed predictions.
For example, you might use digital analytics to identify a cohort of customers who abandon their cart or don't make it through some sort of lead flow. In the adapt/action process, you could remarket to those customers and show them personalized messaging or content. After you “adapt,” the loop continues as you collect more data to see the impact of your action.
Amplitude aims to help customers move from merely reporting on data without taking action to predicting and adapting. According to Adam, organizations will benefit from digital intelligence if they spend most of their time acting based on the insights they collect.
The speakers advised that organizations that want to become more mature need a mindset shift. Instead of considering digital intelligence as a cost center, treat it as a profit center. Companies should see digital intelligence as a source of opportunities to improve the customer experience and increase revenue.
The changing digital intelligence stack
Forrester describes Digital Intelligence Platforms as being made up of three sub-components:
- Data management technology
- Digital analytics technology, and
- Experience optimization technology
While historically, organizations may have worked with a variety of point solutions across CDP, analytics, experimentation and more, Forrester notes an industry-wide shift towards platform consolidation. Forrester also cites a recent uptick in demand for product intelligence specifically. According to Forrester’s 2022 Data And Analytics Survey, 52% of companies have implemented product intelligence solutions, making it one of the most invested-in components in the digital intelligence stack.
Digital intelligence market trends
Adam observed that the Wave aligns with his views on emerging trends in the digital intelligence industry, including the coming together of marketing and product analytics.
As Adam noted, companies are starting to recognize the importance of analytics in both areas and invest in platforms such as Amplitude that offer product and marketing capabilities. He shared that marketing analytics companies like Adobe are expanding into product analytics while product analytics platforms are adding marketing capabilities.
Another change is in the type of data. “The new data model in this digital intelligence world is event-based. Everything revolves around the event,” explained Brandon. Historically product intelligence solutions have been centered around events, while marketing tools have been focused on different types of interactions.
However, companies now need a cross-channel understanding of their customers, which requires a coherent measurement across websites and applications. That's why traditional marketing analytics tools like Google are moving to the event-based tracking model.
Opportunities of AI
Both speakers predict AI will make data analysis more powerful and more accessible.
Brandon outlined two types of AI that will impact the digital intelligence landscape:
- Generative AI, built on large language models
- “Classic AI,” which uses machine learning to carry out predictive analytics and analytics on unstructured data
Brandon expects that the use of classic AI will grow and predictive analytics will become more widespread. Additionally, some vendors will use generative AI in their interfaces, allowing customers to query data in plain English.
Adam agreed, noting that Amplitude is building new product capabilities that will allow people to simply ask questions about their data (instead of creating charts or running queries). The change will make it easier for people who aren't extremely data-savvy or might have been nervous about working with data to get useful responses. You can read more in our announcement here.
AI is already being leveraged across Amplitude. Adam explained that machine learning in the product gives users a starting point when identifying factors that contribute to specific customer behaviors.
For example, if you see a big drop-off between two steps of your conversion funnel, Amplitude can show you all the different events that may be contributing to the drop-off. Though this might not provide a definite answer, it can point you in the right direction so you can take a closer look at the events.
AI also allows Amplitude users to create predictive cohorts. For instance, based on all the signals Amplitude receives from your current customers, you can predict who will likely make a purchase in the next seven days. With that data, you can optimize your marketing actions.
You might decide you don't want to send a discount to those who are highly likely to buy. Meanwhile, for customers who are only 10-20% likely to buy, you can be more proactive and offer a discount coupon.
Watch the full webinar online, or check out our upcoming online and in-person events.
Brandon and Adam wrapped up the discussion by answering some questions from the webinar audience, including the following.
How do you differentiate digital analytics versus digital intelligence?
Digital analytics is a subset of digital intelligence. Digital intelligence requires three layers:
- The data layer
- The analytics layer
- The experience optimization layer
Digital analytics focuses on extracting insights from data that you capture in the data layer, Adam explained. He added that digital analytics is the area that people are most comfortable with, but the problem is that many people stop at analytics without diving into experience optimization. It's using data to optimize and improve customer experience that drives ROI, he said
What are some suggestions for a company looking to get started on improving its competence in digital intelligence?
If you want to get started with digital intelligence, Adam said, it's important to know where you are right now. He recommended identifying how many times in the last month, three months, or six months your organization has done something different in your digital property based on data. If you are not taking action based on data, you know you need to change course.
Brandon also suggested identifying potential use cases for digital intelligence and being as specific as possible because it's often the small details that impact the business. He shared the example of a large North American bank that focused on understanding their digital experience's pain points. They found that customers who had a problem with even small parts of the experience (like resetting a password) were less likely to complete their mortgage application.
What are some of the biggest gotchas when selecting a digital intelligence provider?
Look for a platform that uses the events-based model and allows you to optimize the customer experience in a continuous cycle, Adam and Brandon agreed. Avoid sticking with a familiar tool out of inertia. Instead, go with the provider that fits your needs best.
